Data Engineer

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI solutions, including agentic workflows and RAG pipelines integrated into enterprise systems. The position emphasizes software engineering excellence, cloud-based AI services, and orchestration of LLM capabilities rather than model research. You will build reliable, secure, and observable AI services integrated with internal platforms and APIs. 🗂️ Requirements: 5+ years of professional software development experience, Strong background in designing and operating production systems, Proficiency in Python or another backend language for AI systems, Experience building and integrating RESTful APIs, Understanding of distributed systems fundamentals, Experience with API integrations and event-driven architectures, Solid SQL and database design knowledge, Experience with vector search, Hands-on experience building end-to-end LLM applications, Experience implementing RAG pipelines, Strong knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and regression testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Embeddings, VectorSearch, AzureFunctions, AzureStorage, KeyVault, AppConfiguration, ApplicationInsights 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Full-time remote Senior AI Engineer role focused on designing and operating production-grade GenAI systems, including agentic workflows and RAG pipelines integrated into enterprise platforms. The position emphasizes backend engineering, API integrations, and orchestration of LLM capabilities in secure, scalable cloud environments rather than ML research. The role also includes mentoring engineers and establishing best practices for reliable, observable AI services. 🗂️ Requirements: 5+ years professional software development experience, Proficiency in Python, Experience building production LLM applications, Hands-on experience with RAG systems, Experience designing and integrating RESTful APIs, Strong understanding of distributed systems fundamentals, Experience with SQL databases and performance optimization, Experience with vector search, Experience integrating external services via APIs, Knowledge of Azure cloud services, Experience with unit and integration testing, Ability to build AI evaluation and testing frameworks 📃 Skills: Python, REST, GraphQL, SQL, Azure, RAG, LLM, LangChain, LangGraph, ASP.NET, APIs, Microservices, DistributedSystems, Concurrency, AsyncIO, VectorSearch, Embeddings, Caching, AzureFunctions, Storage, KeyVault, AppConfiguration, ApplicationInsights, ServiceBus, EventHubs 🏢 Description: Workload: full-time Work model: 100% Remote We are seeking a Senior AI Engineer who combines strong software engineering fundamentals with hands-on experience building production GenAI solutions, including agentic workflows and Retrieval-Augmented Generation (RAG). This is an engineering and orchestration role focused on integrating LLM capabilities into enterprise systems – not a traditional model-training/ML research role. 5+ years of professional software development experience (ideally 7+ years across backend/API/integration and cloud platforms). Proven ability to ship production-grade LLM applications ( RAG , tool/function calling, agent orchestration) with reliability, security, and observability. Strong ownership mindset and passion for AI engineering – curiosity, experimentation, and a drive to continuously improve the product and the team. Excellent communication and collaboration skills; ability to guide, mentor, and unblock other engineers as we build out an AI engineering capability. Main Responsibilities: Design, build, and operate agentic AI services that orchestrate tools, workflows, and integrations across cloud systems and enterprise data sources. Implement and continuously improve RAG pipelines for tax artifacts and internal knowledge, including ingestion, retrieval tuning, and evaluation. Integrate AI workflows with existing internal platforms (e.g., assistant frameworks) and back-end services through robust APIs. Define and maintain tool/function schemas and orchestration patterns; implement streaming updates, interrupts, and human-in-the-loop steps as needed. Partner with other engineers to set direction, mentor, and unblock the team — helping establish strong foundations for the AI initiative. Build in quality from day one: automated tests, evaluation checks, monitoring/telemetry, and performance optimization for network-bound workloads. Participate in Agile ceremonies (daily scrums, refinement/grooming, planning) and collaborate through peer review, pair programming, and strong documentation. Apply best practices, design principles, and security standards throughout the SDLC, with a focus on reliability and responsible AI. Key Requirements: Strong software engineering background (not a research-only data science profile): designing, building, and operating production systems. Proficiency in at least one backend language used for AI systems (Python preferred). Hands-on experience building and integrating RESTful APIs ; GraphQL experience is a plus. Strong understanding of distributed systems fundamentals : concurrency, async I/O, resiliency/retries, rate limits, caching, and performance optimization. Experience integrating with external services and internal platforms via APIs and event-driven patterns. Solid database fundamentals (SQL design, performance, migrations); experience with vector search is required, and hybrid search stores are a plus. Hands-on experience building LLM-powered applications end-to-end : prompt design, tool/function interfaces, structured outputs, and streaming user experiences. Experience with RAG systems : document ingestion pipelines, chunking/metadata, embeddings, retrieval strategies, grounding, and evaluation. Cloud services expertise : Strong knowledge of Azure cloud services used for enterprise AI solutions (e.g., Functions, Storage, Key Vault, App Configuration, Application Insights). Development practices experience : Strong background in unit and integration testing; ability to build and maintain AI evaluation harnesses (golden sets, regression tests, automated checks). Nice to Have: Direct experience with LangGraph and/or LangChain for multi-agent workflows. Familiarity with emerging agentic ecosystem concepts/protocols (e.g., MCP, A2A, ADK or similar). Experience integrating AI services into .NET (ASP.NET Core) applications or building AI microservices that serve enterprise applications. Experience with event-driven architectures (service bus, event hubs) and real-time updates/streaming to UI. Experience working with tax/enterprise document corpora and governance constraints (PII, retention, access control). Other Details: This position is designed for remote work and has a flexible duration, allowing for innovation in the AI space within an agile environment.

🏢 Summary: Data Engineer role focused on building and scaling data infrastructure for advanced robotics systems. The position involves designing reliable batch and real-time pipelines, optimizing ETL/ELT processes, and implementing data governance across cloud platforms. You will collaborate cross-functionally to deliver high-quality, scalable data solutions supporting company-wide analytics and operations. 🗂️ Requirements: BS/MS/PhD in Computer Science, Mathematics, Computer Engineering or related field, or equivalent practical experience, 1–5 years of professional experience, Proficiency in Python and SQL, Hands-on experience with Rust, Go, Java, C#, or C++, Experience with Kafka, Spark, and lakehouse formats (Icebert, DeltaLake), Experience with AWS, GCP, or Azure, Strong debugging and problem-solving skills, Willingness to work extended hours and weekends if needed, Ability to work full time onsite in San Francisco 📃 Skills: Python, SQL, Rust, Go, Java, C#, C++, Kafka, Spark, Icebert, DeltaLake, AWS, GCP, Azure, Clickhouse, Flink, Databricks 🏢 Description: About the Role Help us advance our robotics moonshot by scaling our data engineering efforts. Drive design and development of data infrastructure across our products and internal tools. You will play a critical role in working with a cross-functional team to architect and build advanced robotic systems. Responsibilities - Design, build, and maintain scalable, reliable data pipelines that support both batch and real-time analytics. - Develop and optimize ETL/ELT processes to ingest, transform, and integrate data from multiple sources into data warehouses and lakehouse platforms. - Drive and apply best practices in data modeling, pipeline architecture, query optimization, data quality, and data engineering standards. - Collaborate closely with finance, bizops, and engineering teams to understand data needs and deliver solutions. - Provide data engineering support to ensure data accessibility and usability company-wide. - Implement and maintain data governance frameworks to support compliance with internal policies and external regulatory requirements. - Evaluate and adopt modern data engineering technologies, tools, and best practices to improve scalability, reliability, and operational efficiency. - Document data engineering processes, designs, and architectures. Qualifications - BS/MS/PhD in Computer Science, Mathematics, Computer Engineering, or a related field, or equivalent practical experience. - 1-5 years of professional experience. - Proficiency in writing production-grade code in Python and SQL. - Hands-on experience with one of the following languages: Rust, Go, Java, C#, C++. - Strong debugging skills and the ability to diagnose and resolve issues efficiently. - Experience with Kafka, Spark and common lakehouse formats like Icebert, DeltaLake. - Experience working with cloud platforms like AWS, GCP, Azure. Preferred Experience - Experience with Clickhouse, Apache Flink, Databricks. - Experience on financial reporting and understanding of accountability. Additional Requirements - Willing to work extended hours and weekends if needed. - This position is based full time in our San Francisco headquarters. Compensation The pay range for this position at the start of employment is expected to be between $140,000 - $200,000/year. The exact offer may vary depending on job-related knowledge, skills, and experience. In addition to cash compensation, this position will also receive generous equity. Benefits - Unlimited Flexible Time Off. - Health insurance (medical, dental, vision). - Paid parental leave. - Commuter benefits including fully paid parking spots. - Referral bonus. - 401k retirement plan. - Equity program.

🏢 Summary: Senior individual contributor role responsible for designing and owning enterprise-scale data architecture and real-time data pipelines that power a strategic DFM AI + IQE partner integration. The position focuses on building scalable batch and streaming systems, defining data models, and ensuring governance, observability, and CI/CD standards across cross-system integrations. The engineer leads the digital data plane connecting internal platforms with external PLM ecosystems in a high-impact, cloud-native environment. 🗂️ Requirements: Bachelor’s degree in STEM or equivalent experience, Minimum 5 years of experience in data engineering, Deep expertise in Snowflake or similar cloud data warehouse, Expert-level SQL, Strong Python proficiency, Hands-on experience with modern data pipeline tools (dbt, Airbyte, Airflow or similar), Experience designing enterprise data architecture across multiple systems, Knowledge of batch and stream processing systems, Experience with highly scalable data stores, Experience with CI/CD, automated testing, contract testing, schema evolution, Strong knowledge of AWS data ecosystem, Experience integrating with enterprise or partner systems (e.g., PLM, ERP, SaaS) 📃 Skills: Snowflake, SQL, Python, dbt, Airbyte, Airflow, Kafka, Spark, Kinesis, Apache, Iceberg, AWS, Teamcenter, BMIDE, APIs, Looker, Streamlit, Terraform, CloudFormation, CI/CD, CDC 🏢 Description: Xometry is looking for a Staff Data Engineer to join the Data Platform team. This is a senior individual contributor role with broad technical scope and high organizational impact. You will own data architecture decisions, lead the design of scalable pipelines and platforms, and set the engineering bar for how data systems are built and operated. A defining piece of this role is owning the data architecture behind the DFM AI + IQE integration with a strategic partner. You will serve as the data engineering lead for the digital thread connecting the platform to partner ecosystems including Solid Edge, NX, Designcenter, and Teamcenter. You will build the pipelines, contracts, and observability that move quotes, parts, manufacturability signals, and pricing between systems in real time. Responsibilities Lead with technical depth – Design and drive the implementation of enterprise-scale data architecture and engineering solutions spanning multiple systems and domains. Own the partner integration data plane – Architect and build the data layer of the embedded DFM AI + IQE integration with Teamcenter and Designcenter. Own bidirectional pipelines, the joint data model for parts, BOMs, quotes, and manufacturability signals, low-latency feedback paths, and required governance, lineage, and audit controls. Build for scale – Architect and optimize reliable batch and streaming data pipelines, data models, and platforms handling complex, high-volume and event-driven data flows. Own the full lifecycle – Take end-to-end accountability from data acquisition and transformation through delivery, observability, and performance. Set the standard – Define and enforce best practices for data modeling, CI/CD, testing, code quality, contract testing, and schema evolution. Solve ambiguous problems – Navigate cross-domain technical challenges and deliver solutions meeting business and technical objectives. Develop multi-quarter roadmaps – Translate strategic priorities into technical plans and timelines. Collaborate broadly – Partner with engineering, product, data science, business stakeholders, and external partner engineering teams. Mentor and elevate – Guide engineers through design reviews, code reviews, and mentorship. Evaluate and adopt – Recommend tools, platforms, and architectural patterns within the data engineering ecosystem. Qualifications Bachelor's degree in a STEM field (or equivalent experience) and at least 5 years of experience in data engineering with ownership of large-scale data systems. Deep expertise with cloud data warehouses, preferably Snowflake, including optimization and performance tuning. Expert-level SQL and strong Python proficiency. Experience building and optimizing data pipelines and architectures using tools such as dbt, Airbyte, or Airflow. Experience planning and implementing enterprise data architecture across multiple systems and organizational boundaries. Working knowledge of queueing, batch and stream processing (Kafka, Spark, Kinesis) and scalable data stores (Apache Iceberg). Experience developing database-heavy services or APIs with focus on testability and maintainability. Strong understanding of CI/CD, automated testing, contract testing, and schema evolution in data pipelines. Strong knowledge of AWS data ecosystem and cloud-native infrastructure. Enterprise integration experience with PLM, ERP, or large SaaS systems; Teamcenter experience is a strong plus. Familiarity with data visualization tools such as Looker or Streamlit. Experience with data governance, data quality frameworks, and observability tooling. Exposure to lakehouse or data mesh architectures. Experience with infrastructure as code frameworks such as Terraform or CloudFormation. Experience with event-driven architecture, CDC pipelines, and low-latency operational data flows. Benefits Base salary range: $180,000–$200,000 annually plus commission, depending on experience and location. Competitive benefits package including 401(k) match, medical, dental, and vision insurance; life and disability insurance; generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave; employee assistance program and additional wellbeing resources.

🏢 Summary: Senior individual contributor role leading enterprise-scale data architecture and real-time partner integrations, owning the design of scalable batch and streaming pipelines across systems. Responsible for building and operating the data plane behind a strategic DFM AI + IQE integration, enabling low-latency, bidirectional data flows between platforms. Sets engineering standards for data modeling, CI/CD, governance, and observability while collaborating cross-functionally. 🗂️ Requirements: Bachelor's degree in STEM or equivalent experience, 5+ years in data engineering with ownership of large-scale data systems, Deep expertise in Snowflake and cloud data warehouses, Expert-level SQL, Strong Python proficiency, Experience building and optimizing modern data pipelines (dbt, Airbyte, Airflow or similar), Experience designing enterprise data architecture across multiple systems and partner boundaries, Knowledge of batch and stream processing systems, Experience with highly scalable data stores, Experience writing database-heavy services or APIs, Strong understanding of CI/CD, automated testing, contract testing, schema evolution, Strong knowledge of AWS and cloud-native infrastructure, Enterprise or partner system integration experience (PLM, ERP, or SaaS), Experience with infrastructure as code frameworks, Experience with event-driven architectures and CDC pipelines 📃 Skills: Snowflake, SQL, Python, dbt, Airbyte, Airflow, Kafka, Spark, Kinesis, Apache, Iceberg, AWS, Terraform, CloudFormation, Teamcenter, BMIDE, APIs, CI/CD, CDC, Looker, Streamlit 🏢 Description: Xometry is looking for a Staff Data Engineer to join the Data Platform team. This is a senior individual contributor role with broad technical scope and high organizational impact. You will own data architecture decisions, lead the design of scalable pipelines and platforms, and set the engineering bar for how data systems are built and operated. A defining piece of this role is owning the data architecture behind the DFM AI + IQE integration with a strategic partner. You will serve as the data engineering lead for the digital thread connecting the platform to partner ecosystems including Solid Edge, NX, Designcenter, and Teamcenter, building pipelines, data contracts, and observability to move quotes, parts, manufacturability signals, and pricing data in real time. Responsibilities - Lead the design and implementation of enterprise-scale data architecture and engineering solutions across multiple systems and domains - Architect and build the data layer for embedded DFM AI + IQE integrations, including bidirectional pipelines and joint data models for parts, BOMs, quotes, and manufacturability signals - Design low-latency signal paths delivering DFM and pricing feedback into designer environments - Establish governance, lineage, and audit capabilities for partner-integrated data systems - Architect and optimize reliable batch and streaming pipelines for complex, high-volume, event-driven data flows - Own the full lifecycle of data engineering work from ingestion and transformation to delivery and observability - Define and enforce best practices for data modeling, CI/CD, testing, code quality, contract testing, and schema evolution - Solve complex cross-domain technical challenges aligned with business objectives - Develop multi-quarter technical roadmaps and execution plans - Collaborate with engineering, product, data science, business stakeholders, and partner engineering teams - Mentor engineers through design and code reviews - Evaluate and recommend tools, platforms, and architectural patterns Qualifications - Bachelor's degree in a STEM field (or equivalent experience) - At least 5 years of experience in data engineering with ownership of complex, large-scale systems - Deep expertise in Snowflake, including optimization and performance tuning - Expert-level SQL and strong Python proficiency - Experience with modern data tooling such as dbt, Airbyte, and Airflow - Experience designing enterprise data architectures spanning multiple systems and partner boundaries - Knowledge of batch and stream processing technologies (e.g., Kafka, Spark, Kinesis) and scalable data stores (e.g., Apache Iceberg) - Experience building database-heavy services or APIs with focus on testability and maintainability - Strong understanding of CI/CD, automated testing, contract testing, and schema evolution in data pipelines - Strong knowledge of AWS and cloud-native infrastructure - Enterprise integration experience with PLM, ERP, or large SaaS systems; Teamcenter experience is a strong plus - Familiarity with data visualization tools such as Looker or Streamlit - Experience with data governance, data quality frameworks, and observability tooling - Exposure to lakehouse or data mesh architectures - Experience with infrastructure as code (Terraform, CloudFormation) - Experience with event-driven architectures, CDC pipelines, and low-latency operational data flows Benefits - Estimated base salary range: $180,000–$200,000 annually plus commission, depending on experience and location - Competitive benefits package including 401(k) match - Medical, dental, and vision insurance - Life and disability insurance - Generous paid time off including vacation, sick leave, floating and fixed holidays, maternity and bonding leave - Employee assistance and wellbeing resources

🏢 Summary: Opportunity to join a newly formed AI team in the banking sector to build a modern AI-native platform from scratch. The role focuses on designing and delivering production-grade solutions using LLMs, RAG, and agent-based architectures, while shaping AI strategy and architectural decisions. You will develop secure, transparent, and scalable AI systems that drive real business value in a regulated financial environment. 🗂️ Requirements: At least 3 years of experience in AI/ML, Minimum 5 years of experience in product development, Strong Python skills, Hands-on experience with LLMs, RAG, and agent-based systems in production, Experience with AI frameworks such as Agno, LangChain, LlamaIndex or similar, Knowledge of prompt engineering and AI model evaluation, Experience with Azure or AWS, Understanding of vector databases and embeddings, Experience with workflow orchestration tools (Temporal, Prefect, Airflow), Ability to design scalable and reliable AI solutions, Experience in model monitoring and MLOps practices, Ability to make architectural decisions and assess business value of AI, Fluent English 📃 Skills: Python, LLM, RAG, LangChain, LlamaIndex, Agno, Azure, AWS, Temporal, Prefect, Airflow, MLOps, Embeddings, VectorDB 🏢 Description: We are looking for an experienced Senior AI Engineer to join a newly formed AI team delivering a strategic initiative in the banking sector. This is a unique opportunity to co-create a modern AI-native platform from scratch and influence the direction of AI within the organisation. In this role, you will design and develop solutions based on LLMs, RAG systems, and agent-based architectures to support data integration and transformation processes. You will contribute to key decisions around AI strategy, model selection, architecture, and quality standards. We are seeking a candidate with strong technical skills and hands-on experience in building production-grade AI solutions—someone who understands where AI brings real business value and can deliver high-quality, transparent, and secure solutions in a financial environment. Your tasks Design and develop solutions based on LLMs, RAG, and agent-based architectures Co-create and execute an AI strategy for a modern banking platform Select models, frameworks, and approaches for production-grade AI solutions Build systems for data integration, transformation, and validation automation Define prompt engineering, model evaluation, and AI quality standards Develop monitoring, evaluation, and continuous improvement mechanisms Collaborate with engineering and product teams on new features Ensure high quality, transparency, and auditability of AI outputs Contribute to key architectural decisions and AI direction Mentor and share knowledge within the AI team Requirements At least 3 years in AI/ML and a minimum of 5 years in product development Strong Python skills Hands-on experience with LLMs, RAG, and agent-based systems in production Familiarity with frameworks such as Agno, LangChain, LlamaIndex, or similar Knowledge of prompt engineering and AI model evaluation Experience with Azure or AWS Understanding of vector databases and embeddings Experience with workflow orchestration tools (e.g., Temporal, Prefect, Airflow) Ability to design scalable, reliable AI solutions Experience in model monitoring and MLOps practices Capability to make architectural decisions and assess the business value of AI Strong collaboration skills with technical and business stakeholders Fluent English Nice-to-have requirements Previous work in financial services, fintech, or other regulated industries Knowledge of compliance, auditability, and AI security Familiarity with MLOps and large-scale ML/LLM deployments Experience fine-tuning open-source models for specific domains Proven track record in developing AI solutions for data platforms, analytics, or SaaS products Background in AI R&D projects Publications, conference speaking, or open-source contributions Experience building and scaling technical teams What we offer Great Place to Work since 2015 - it’s thanks to feedback from our workers that we get this special title and constantly implement new ideas Employment stability - revenue of PLN 2.1BN, no debts, since 2006 on the market We share the profit with Workers - over PLN 76M has already been allocated for this aim since 2022 Attractive benefits package - private healthcare, benefits cafeteria platform, car discounts and more Comfortable workplace – class A offices or remote work Dozens of fascinating projects for prestigious brands from all over the world PLN 1 000 000 per year for your ideas - with this amount, we support the passions and voluntary actions of our workers Investment in your growth – meetups, webinars, training platform and technology blog – you choose Fantastic atmosphere created by all Sii Power People If you want to work on systems with high operational significance — apply now!

🏢 Summary: Lead Data Engineer role focused on driving AI initiatives and building scalable cloud-based data architectures in a global environment. The position involves technical ownership of data platforms, designing secure and high-performing systems, and leading data engineering efforts in a DevOps setting. The role emphasizes AI integration, cloud infrastructure, and enterprise-grade data governance. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python in production, Strong experience designing and scaling complex data systems, Hands-on experience with AI technologies, Hands-on experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs and data integration, Experience with automation tools, Knowledge of data governance practices, Understanding of data security and compliance standards, Proven experience leading and mentoring engineers 📃 Skills: Python, SQL, AWS, Azure, Java, AI, RAG, MCP, APIs, DevOps, Automation, Monitoring, Cloud, DataEngineering, DataPipelines, Governance, Security, Compliance, Backend 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Lead Data Engineer role focused on building scalable AI and cloud-based data solutions in a global environment. The position involves leading data engineering initiatives, designing secure cloud architectures, and supporting AI applications using AWS or Azure. The offer includes hybrid work, professional development opportunities, and a comprehensive benefits package. 🗂️ Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience, 8+ years in software engineering, 5+ years of backend development with Python, Experience designing and scaling complex data systems, Hands-on experience with AI technologies, Experience with AWS or Azure, Strong knowledge of Python and SQL, Experience with APIs, data integration, automation tools, and data governance, Understanding of data security and compliance standards, Leadership and mentoring experience, English and Polish proficiency (minimum B2) 📃 Skills: Python, SQL, AWS, Azure, Java, APIs, DevOps, AI, RAG, MCP, Automation, DataGovernance 🏢 Description: We are looking for an experienced Lead Data Engineer to drive AI and cloud-based data solutions within a global technology organization. In this role, you will lead data initiatives, shape scalable architectures, and collaborate with both technical teams and senior stakeholders to deliver secure and high-performing systems. Key Responsibilities: Act as the main point of contact for data access and system-related topics with senior stakeholders Lead and mentor data engineers, promoting best practices and technical excellence Design, build, and maintain scalable cloud infrastructure and data pipelines Ensure data quality, security, compliance, and governance across the full lifecycle Develop secure and reliable cloud architectures (AWS/Azure) for AI and enterprise applications Implement monitoring, alerting, disaster recovery, and business continuity solutions Take technical ownership of applications within a DevOps environment Drive automation and self-service capabilities Support AI initiatives (e.g., AI Agents, RAG, MCP) with focus on quality and scalability Stay updated on emerging technologies and advise on strategic data direction Requirements: Degree in Computer Science, AI, Data Science, Software Engineering, or equivalent experience 8+ years in software engineering, including 5+ years of backend development with Python (production level) Strong experience designing and scaling complex data systems Hands-on experience with AI technologies and cloud platforms (AWS or Azure) Solid knowledge of Python, SQL (Java is a plus) Experience with APIs, data integration, automation tools, and data governance Strong understanding of data security and compliance standards Proven leadership and mentoring experience Excellent communication skills in English and Polish (min. B2); German is a plus What We Offer: Opportunity to work in a global, international environment Real impact on AI and cloud solutions in a large-scale organization Access to training platforms and professional development programs Hybrid work model with flexible hours (modern office in central Wroclaw) Comprehensive benefits package (medical & dental care, sports card, life insurance, mental health program) Cafeteria benefits platform with monthly points CSR initiatives, integration events, and employee passion clubs

🏢 Summary: Senior Data Platform Engineer role focused on building and optimising a cloud-native lakehouse platform for large-scale analytics and reporting. The position involves designing distributed data pipelines, enabling self-service analytics, and implementing governance and observability frameworks using modern data technologies. You will work with Spark-based systems and integrated data warehousing solutions to deliver scalable, reliable data platforms. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Hands-on experience with Apache Spark in production environments, Experience with Delta Lake and/or Apache Iceberg in production, Practical experience with dbt for data transformations, Experience with Databricks and Snowflake, Understanding of data governance and lineage in large-scale environments, Familiarity with Kubernetes and Docker, Experience with CI/CD and automated testing practices, Ability to participate in on-call rotations 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD 🏢 Description: ABOUT THE COMPANY We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response. We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the platforms you build will have real consequence across the organisation. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As a Senior Data Platform Engineer, you'll combine strong software engineering principles with deep data expertise to build robust, cloud-native platforms that process large-scale datasets efficiently and enable internal teams to build reporting and analytics on top of them. The role emphasises cloud-native architecture, lakehouse integration, data warehousing, and governance best practices. You'll work on systems using Apache Spark, Delta Lake, and Iceberg, and help deliver curated data models and self-service analytics capabilities to internal stakeholders. You'll also participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems Design and implement scalable data pipelines and distributed systems using Spark and Python to process and transform large-scale datasets for analytics and reporting. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Iceberg, ensuring data reliability, versioning, and performance optimisation at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Collaborate with internal teams to deliver curated datasets and self-service analytics capabilities for reporting and advanced use cases. Data warehousing optimisation Integrate and optimise Databricks and Snowflake for scalable storage and query performance. Drive performance tuning and cost optimisation across Spark jobs and cloud-native environments. Governance and observability Implement observability and governance frameworks including data lineage, quality checks, and compliance controls. Build platforms that allow secure and compliant access to diverse data sources. Engineering best practices Apply and champion clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. On-call participation Participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT WE LOOK FOR Python and SQL Strong programming skills in both Python and SQL, applied to production data platform work at scale. Apache Spark Solid hands-on experience with Spark for distributed data processing, including performance tuning in production environments. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You've applied these in production and understand the trade-offs in real-world scenarios. dbt and analytics tooling Practical experience with dbt for transformation workflows. Familiarity with Databricks and Snowflake for large-scale analytics workloads. Data governance and compliance Understanding of data governance, lineage tracking, and compliance requirements in large-scale, multi-tenant data environments. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. THE TEAM You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing. COMPENSATION & BENEFITS Salary 208,000 – 312,000 PLN per year, plus an annual performance bonus and long-term incentives. Health coverage Comprehensive health, dental, and vision plans. Parental leave Parental leave available for both primary and secondary caregivers. Flexible working Flexible work arrangements with a remote-first model. Company breaks Two week-long company-wide breaks per year, plus additional time off. Training investment Dedicated training investment programme to support ongoing professional development.

🏢 Summary: Senior Data Engineer role supporting a DoD client, focused on building secure metadata extraction, ingestion, and integration pipelines within an enterprise data governance and federated catalog ecosystem. The position involves developing scalable automation workflows, lineage tracking, and schema extraction solutions aligned with centralized repository and cloud ingestion requirements. This role is contingent upon contract award and emphasizes secure, compliant data engineering practices. 🗂️ Requirements: Proven experience building and managing data pipelines, Hands-on experience with ETL/ELT processes, Experience developing metadata harvesting solutions, Strong proficiency in SQL, Strong proficiency in Python and/or R, Experience with AWS and/or Azure cloud platforms, Experience implementing API-based data exchange, Experience with lineage tracking and metadata synchronization, Strong knowledge of data governance frameworks and metadata standards, Experience working with legacy and distributed data environments, Eligibility for Tier 1 background investigation 📃 Skills: SQL, Python, R, AWS, Azure, ETL, ELT, APIs, Metadata, Lineage, Automation, Schemas, DataGovernance, Cloud, AI 🏢 Description: Andrew Morgan, LLC is a rapidly growing Service-Disabled Veteran-Owned Small Business (SDVOSB) and HUBZone-certified organization. We are seeking a qualified Senior Data Engineer to support a potential contract award with a DOD Client. This role is contingent upon contract award and will play a critical part in our efforts to deliver exceptional results for this opportunity. The Senior Data Engineer leads technical metadata extraction, pipeline development, and secure data integration activities supporting DHA's enterprise data governance and federated catalog ecosystem. Execute technical metadata extraction and structured discovery from DHA data sources. Develop ingestion pipelines, validation scripts, and migration workflows for the centralized repository. Create automation pipelines and harvesting connectors for metadata extraction and tagging. Implement secure metadata exchange pipelines and lineage propagation for federated catalogs. Develop and test lifecycle automation scripts, validation pipelines, and governance workflows. Support automated schema extraction, lineage capture, and AI-assisted enrichment. Ensure automation pipelines are scalable and compatible with DHA-EDC ingestion requirements. Collaborate with governance leads to align engineering workflows with validated governance decisions. REQUIREMENTS: Proven expertise in building and managing data pipelines, ETL/ELT processes, and metadata harvesting solutions. Skilled in SQL, Python, and/or R for data engineering and automation. Hands-on experience with cloud data platforms (AWS and/or Azure) and enterprise integration patterns. Proficient in implementing API-based data exchange, lineage tracking, and metadata synchronization. Strong grasp of data governance frameworks and metadata standards. Experience with legacy, heterogeneous, and distributed data environments. Preferred background in DoD, federal healthcare, or compliance-driven settings. Must be eligible for Tier 1 background investigation. SALARY: Salary is commensurate with both location and experience. THE AM EMPLOYEE WILL DISPLAY… Attention to Detail: Produce high-quality deliverables and outputs that align with contract outcomes. Self-Sufficiency: Execute tasks independently, seeking client assistance only after internal resources are exhausted, ensuring requests align with contract goals. Teamwork: Collaborate effectively with team members, including AMC resources, subcontractors, and government stakeholders. Communication/Engagement: Maintain professional conduct in meetings and written communication, participating actively with cameras on. Responsiveness: Stay engaged, communicate promptly, and ensure deadlines are consistently met. ABOUT ANDREW MORGAN… Andrew Morgan, LLC, founded in 2017 and headquartered in Alexandria, VA, is a Service-Disabled Veteran Owned Small Business (SDVOSB) and a certified HUBZone Small Business. We specialize in delivering high-quality consulting services to both federal and commercial clients, offering expertise in Strategy and Management Consulting, Technology & Architecture Services, and Industry & Mission Analytics Solutions. Our distinguished clientele includes the Department of Veterans Affairs (VA), National Aeronautics and Space Administration (NASA), the Department of Defense (DoD), and the United Stated Army Corps of Engineers (USACE). We are committed to providing innovative solutions and exceptional service to support our clients' missions and objectives. BENEFITS: 15 days of Paid Time Off + 11 Paid Federal Holidays 401K Program (up to 5% employer matching) Three Gold Healthcare Options (with 75%-90% employer-paid premiums) Flexible Spending Account / Dependent Care Assistance Program Employer Paid Short Term Disability Professional Training and Development Corporate Team Building Events And MORE! Join AM Today! EQUAL OPPORTUNITY EMPLOYER: Andrew Morgan Consulting does not discriminate in employment opportunities, terms and conditions of employment, or practices. All qualified applicants will receive consideration for employment without regard to race, age, gender, religious or political beliefs, national origin or heritage, disability, sexual orientation, protected veteran status, or any characteristic protected by law.