Data Engineer

🏢 Summary: The offer is for an experienced Python Data Engineer to build scalable, cloud-based data and analytics solutions for global financial institutions. The role focuses on designing distributed data pipelines, enhancing system reliability, and developing financial and AI-driven data platforms. You will work with modern cloud and AI tools to advance enterprise data architecture and analytics capabilities. 🗂️ Requirements: 4+ years of professional experience in Python data or software engineering, Strong knowledge of data architecture, data modeling, and data warehousing, Advanced SQL skills and complex query writing, Experience building scalable distributed data pipelines, Hands-on experience with cloud environments (AWS preferred), Understanding of event-driven architectures, Experience with debugging and system reliability practices 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 Summary: Opportunity for an experienced Python Data Engineer to build scalable data platforms and analytics systems for global financial institutions. The role focuses on designing cloud-based data pipelines, enhancing system reliability, and integrating modern AI tools into engineering workflows. You will collaborate across distributed teams to deliver high-quality solutions in enterprise data, risk analytics, and AI-driven metadata applications. 🗂️ Requirements: 4+ years of professional experience in software or data engineering using Python, Strong knowledge of data architecture, data modeling, and data warehousing, Ability to write complex SQL queries and perform advanced debugging, Experience building scalable, distributed data pipelines in cloud environments, Experience with AWS, Familiarity with event-driven architectures 📃 Skills: Python, SQL, AWS, Databricks, Spark, PySpark, Scala, Delta, Airflow, dbt, Kafka, Kubernetes, MongoDB, Grafana, Loki, Prometheus, OpenTelemetry 🏢 Description: We are partnering with top-tier global financial institutions to scale their core technology and data infrastructure. We are looking for an experienced and product-oriented Python Data Engineer to join our technology group. In this role, you will work at the intersection of cutting-edge technology and institutional finance. You will collaborate closely with data consumers, engineering teams, and business stakeholders to push the firm's technological capabilities forward. What You’ll Do: Core Responsibilities: Design, develop, and deliver high-quality, scalable Python-based solutions. Drive engineering excellence by ensuring system reliability, automating processes, and maintaining high operational standards. Actively experiment with and integrate modern AI coding tools (e.g., Copilot, Cursor) to streamline engineering workflows. Lead design discussions, mentor junior colleagues, and communicate proactively across a geo-distributed team. Depending on the specific project or team, your focus may include: Enterprise Data Platforms: Building cloud-based (AWS) pipelines for data ingestion, streaming, and cataloging. Risk & Portfolio Analytics Systems: Developing software for financial data ingress/egress, performance/exposure monitoring, and automated reconciliation. AI & Metadata Applications: Extending AI-powered semantic data access layers and internal data catalogs. What We’re Looking For: Experience: 4+ years of professional experience in software or data engineering, specifically using Python . Data Skills: Solid understanding of data architecture, modeling, and warehousing. Excellent debugging acumen and comfort writing complex SQL statements. Cloud & Architecture: Experience building scalable, distributed pipelines in a cloud environment (preferably AWS ). Familiarity with event-driven architectures. Mindset: Impact-oriented, proactive, self-starting learner who embraces engineering automation, navigates ambiguity well, and holds themselves to high ethical standards. Nice to Have: Big Data & Orchestration: Expertise in Databricks, Spark (PySpark/Scala), Delta Lake, and orchestration tools like Airflow, dbt, or Kafka. Infrastructure & Observability: Working knowledge of Kubernetes, MongoDB, and observability stacks (Grafana, Loki, Prometheus, OpenTelemetry). Offer: Competitive compensation (30k - 45k PLN) with flexible contracting options (B2B/UoP). Premium office location in the heart of Warsaw. Comprehensive private medical and dental care. Sports card and wellness benefits. Private life insurance

🏢 Summary: Design and scale high-throughput data pipelines on cloud platforms to support advanced analytics and AI-driven products. The role focuses on building distributed data architectures in AWS and Databricks, ensuring performance, governance, and data quality. You will collaborate with AI/ML teams to deliver scalable, production-grade data solutions. 🗂️ Requirements: 3+ years of data engineering experience, Strong Python programming skills, Experience with Spark or Scala, Experience building distributed data pipelines in cloud environments, Knowledge of data modeling and data warehousing principles, Bachelor’s or Master’s degree in Computer Science or Engineering 📃 Skills: Python, Spark, Scala, AWS, Glue, EMR, Fargate, StepFunctions, Databricks, SQL, APIs, GenAI, GraphDB 🏢 Description: Data Engineer – Cloud & AI Platforms We’re looking for a Data Engineer to design and scale high-throughput data pipelines supporting advanced analytics and AI-driven products. What You’ll Do Architect and maintain distributed data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions) Ingest and process large volumes of structured and unstructured data (internal, market, third-party, alternative sources) Collaborate with AI/ML and engineering teams to design scalable data architectures and APIs Optimize performance and cost using Spark and cloud-native best practices Implement data governance, privacy, lineage, and access controls Build automated validation, monitoring, and data quality frameworks Evaluate emerging GenAI and data tooling to enhance platform capabilities What You Bring 3+ years of experience in data engineering Strong Python and experience with Spark or Scala Proven experience building distributed pipelines in cloud environments Solid understanding of data modeling, architecture, and warehousing principles Innovative problem-solving mindset Bachelor’s or Master’s degree in Computer Science or Engineering Nice to have: Experience with graph databases.

🏢 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 Data Engineer role focused on designing and building scalable serverless data ingestion pipelines in AWS within the healthcare domain. The position emphasizes strong Python engineering, cloud architecture leadership, and implementation of modern data platforms and DevOps practices. The role involves driving technical excellence and delivering reliable, high-impact data solutions in an international environment. 🗂️ Requirements: 10+ years of experience in Python programming, Strong software engineering skills in data processing, Extensive experience with AWS Cloud and Serverless Architecture, Hands-on experience with AWS Lambda, S3, and Cognito, Experience building E2E automated tests for data pipelines, Practical knowledge of Data Mesh and Medallion Architecture, Experience with Infrastructure as Code using AWS CDK or Terraform, Experience with CI/CD pipelines using GitLab or GitHub Actions, Experience with ETL/ELT processes and dbt, Experience working with GraphQL, Minimum B2 level English proficiency 📃 Skills: Python, AWS, Lambda, S3, Cognito, Boto3, DataMesh, Medallion, CDK, Terraform, GitLab, GitHubActions, ETL, ELT, dbt, GraphQL, CI/CD 🏢 Description: We are looking for a highly skilled Data Engineer to join our client in the healthcare sector. Our requirements: Technical Expertise: Python Programming: 10+ years of experience with strong Software Engineering skills focused on data processing. AWS & Serverless: Extensive experience with AWS Cloud, specifically focusing on Serverless Architecture and services (including AWS Lambda , AWS S3 Tables , and AWS Cognito ). Automated Testing: Proven experience in developing End-to-End (E2E) automated tests to ensure pipeline reliability, utilizing tools such as Boto3 for AWS resource validation. Data Concepts: Practical knowledge of Data Mesh and Medallion Architecture , along with general data processing and analysis. DevOps & IaC: Hands-on experience with Infrastructure as Code ( AWS CDK or Terraform ) and CI/CD pipelines ( GitLab pipelines or GitHub Actions ). Modern Tooling: Experience with ETL/ELT solutions, dbt , and GraphQL . Communication & Soft Skills: English Language: Minimum B2 level , enabling smooth daily technical and business communication in a global environment. Collaboration: Excellent communication skills and the ability to thrive in a collaborative, international team. Standards: A strong commitment to high standards of ethics, quality (Clean Code), and reliable delivery. Nice to have: Experience with Snowflake and SQL . Knowledge of Data Vault 2.0 modeling. Experience with Databricks . Familiarity with the Microsoft ecosystem: C# / .Net, T-SQL, SQL Server , and Azure DevOps . Experience with Star Schema database modeling. Knowledge of Descriptive Statistics. Your responsibilites: Design and build scalable Data Ingestion pipelines within the AWS cloud ecosystem. Lead technical delivery and implementation of core platform components, ensuring architectural integrity across the entire data lifecycle. Collaborate with Engineering Managers and cross-functional teams across the globe and Poland. Drive technical excellence by improving team processes, architecture standards, and engineering best practices. Support and consult with stakeholders to ensure successful delivery of high-impact, data-driven solutions. Contribute to the growth and maturity of the team’s cloud and data engineering capabilities. We offer: Challenging role within the company that creates innovative solutions. Work in international environment on demanding projects. Remote work model. Subsidized private medical care, life insurance, multisport card. Integration meetings. Employee referral program. If you have a deep expertise in Python and AWS , and building scalable Serverless data architectures is where you truly excel, this is the perfect role for you!

🏢 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: Python Software Engineer role focused on building and operating production-grade Python applications, APIs, and data pipelines in a governed data platform environment. The position involves transforming data science prototypes into deployable services, optimizing PySpark workloads, and collaborating with platform teams on Databricks and CI/CD practices. The offer includes flexible remote work, career development programs, certifications, and comprehensive benefits. 🗂️ Requirements: 3+ years of Python engineering experience, Experience with Python packaging, Knowledge of typing and clean architecture, Proficiency in error handling and performance-oriented development, Experience with Git workflows, Experience with automated testing, Experience with CI/CD, Expertise in Pandas, Expertise in NumPy, Experience with Parquet data formats, Experience building APIs or services, Experience with FastAPI, Flask or similar frameworks, Experience working in Databricks or containerized environments 📃 Skills: Python, Pandas, NumPy, Parquet, FastAPI, Flask, Databricks, Spark, PySpark, Git, CI/CD, APIs, SDLC, scikit-learn 🏢 Description: We are seeking a Python Software Engineer to join our Production Data & Model Services team. In this role, you will build and operate production-grade Python applications, transform data science prototypes into deployable services and collaborate with platform teams to deliver robust data pipelines and APIs. Responsibilities Build and run production-grade Python applications (APIs and batch jobs) with strong SDLC practices including code reviews, testing, CI/CD, observability and documentation Develop robust data pipelines (batch and near-real-time) reading and writing governed storage with Parquet/columnar formats and approved patterns Transform quant and data science prototypes into deployable packages/services (typed, modular, versioned) Expose scoring and analytics via APIs or scheduled jobs rather than notebook-only deliverables Collaborate with platform teams on Databricks/Spark connectivity Optimize PySpark workloads when needed Ensure release discipline through Git workflows, automated tests and code reviews Requirements 3+ years of strong Python engineering experience including packaging (wheels/pyproject), typing and clean architecture Proficiency in error handling and performance-oriented development Proven production SDLC background with Git workflows, automated tests and CI/CD Expertise in Pandas and NumPy in production pipelines Familiarity with data formats like Parquet and governed data access patterns Experience building and operating APIs/services using FastAPI, Flask or similar frameworks Competency working in governed platform environments such as Databricks or containerized dev platforms Nice to have Skills in scikit-learn for production feature and scoring pipelines, including reproducible transforms and model packaging/versioning Background in PySpark and distributed processing Knowledge of IDE-to-Databricks workflows such as Databricks Connect We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: The offer is for a Python Software Engineer to build and operate production-grade applications and data pipelines within a Production Data & Model Services team. You will transform data science prototypes into deployable services, expose analytics via APIs or scheduled jobs and collaborate with platform teams in governed environments. The role emphasizes strong SDLC practices, CI/CD, and scalable data processing with Python and Spark-based technologies. 🗂️ Requirements: 3+ years of Python engineering experience, Experience with Python packaging (wheels, pyproject), typing and clean architecture, Strong production SDLC experience with Git workflows, automated tests and CI/CD, Proficiency in error handling and performance-oriented development, Expertise in Pandas and NumPy in production pipelines, Experience with Parquet and governed data access patterns, Experience building and operating APIs/services with FastAPI, Flask or similar, Experience working in governed platforms such as Databricks or containerized environments 📃 Skills: Python, Pandas, NumPy, Parquet, FastAPI, Flask, PySpark, Databricks, Git, CI/CD, Spark, scikit-learn, GCP, Azure, AWS 🏢 Description: We are seeking a Python Software Engineer to join our Production Data & Model Services team. In this role, you will build and operate production-grade Python applications, transform data science prototypes into deployable services and collaborate with platform teams to deliver robust data pipelines and APIs. Responsibilities Build and run production-grade Python applications (APIs and batch jobs) with strong SDLC practices including code reviews, testing, CI/CD, observability and documentation Develop robust data pipelines (batch and near-real-time) reading and writing governed storage with Parquet/columnar formats and approved patterns Transform quant and data science prototypes into deployable packages/services (typed, modular, versioned) Expose scoring and analytics via APIs or scheduled jobs rather than notebook-only deliverables Collaborate with platform teams on Databricks/Spark connectivity Optimize PySpark workloads when needed Ensure release discipline through Git workflows, automated tests and code reviews Requirements 3+ years of strong Python engineering experience including packaging (wheels/pyproject), typing and clean architecture Proficiency in error handling and performance-oriented development Proven production SDLC background with Git workflows, automated tests and CI/CD Expertise in Pandas and NumPy in production pipelines Familiarity with data formats like Parquet and governed data access patterns Experience building and operating APIs/services using FastAPI, Flask or similar frameworks Competency working in governed platform environments such as Databricks or containerized dev platforms Nice to have Skills in scikit-learn for production feature and scoring pipelines, including reproducible transforms and model packaging/versioning Background in PySpark and distributed processing Knowledge of IDE-to-Databricks workflows such as Databricks Connect We offer We gather like-minded people: Engineering community of industry professionals Friendly team and enjoyable working environment Flexible schedule and opportunity to work remotely within Poland Chance to work abroad for up to 60 days annually Business-driven relocation opportunities We provide growth opportunities: Outstanding career roadmap Leadership development, career advising, soft skills, and well-being programs Certification (GCP, Azure, AWS) Unlimited access to LinkedIn Learning, Get Abstract, Cloud Guru English classes We cover it all: Stable income (Employment Contract or B2B) Participation in the Employee Stock Purchase Plan Benefits package (health insurance, multisport, shopping vouchers) Strategically located offices featuring entertainment and relaxation zones, table tennis and football, free snacks, fantastic coffee, and more Referral bonuses Corporate, social and well-being events Please, note: The set of bonuses might vary based on the role you apply for – specifics will be discussed with our recruiter during the general interview. We will reach out to selected candidates exclusively. EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

🏢 Summary: Senior Python Data Engineer role focused on building and maintaining scalable data-driven applications and regulatory reporting solutions within an investment banking environment. The position involves developing reliable data pipelines, working with big data technologies, and contributing across the full software development lifecycle in a hybrid work model. 🗂️ Requirements: Bachelor's degree in Computer Science or equivalent IT field, 5+ years of experience in a similar role, Experience with Big Data, Data Warehouse and Data Lake, Hands-on experience building scalable data pipelines, Experience processing high-volume batch and streaming data, Expertise in Databricks, Expertise in Python, Expertise in Spark, Familiarity with Delta Lake, Familiarity with DLT, Familiarity with GitLab, Knowledge of Azure cloud technologies, Knowledge of Unix/Linux, Shell scripting skills, Experience designing high-throughput and low-latency applications, Experience building automated functional testing and CI/CD pipelines, Ability to implement prototypes and iterate using engineering best practices, Hands-on usage of AI in engineering SDLC, English proficiency at B2 level or higher 📃 Skills: Python, Spark, Databricks, Delta, DLT, GitLab, Azure, Unix, Linux, Shell, CI/CD, SQL, PLSQL, PostgreSQL 🏢 Description: We are seeking a hands-on Senior Python Data Engineer to join the Regulatory Reporting team in Poland within the Investment Bank's Digital Operations Stream, working to transform and improve products and platforms relied on by Regulatory and Data Clients. Working from the client's office is required 3 days per week. Responsibilities - Design, implement and maintain new and existing data-driven applications - Develop and deliver solutions end to end - Engineer reliable data pipelines for sourcing, processing, distributing and storing data - Design data models that can support ever-growing volumes - Contribute to all stages of the software development lifecycle - Provide technical expertise, recommendations and innovative solutions - Collaborate with the product owner and other technologists - Share expertise and best practice with colleagues and contribute regularly to the engineering culture Requirements - Hold a Bachelor's degree in Computer Science or equivalent in the IT field with 5+ years of experience in a similar role - Background in Big Data, Data warehouse and Data lake - Showcase of hands-on experience building scalable data pipelines, processing high volume data in batch and stream for near real-time analytics - Expertise in Databricks, Python and Spark - Familiarity with Delta Lake, DLT and GitLab - Knowledge of Cloud technologies such as Azure, Unix/Linux and shell scripting - Expertise designing applications considering NFRs around high throughput and low latency for data processing - Expertise building automated functional testing and CI/CD pipelines using industry standard tools - Capability to quickly implement prototypes and iterate to harden the product with good engineering principles - Hands-on usage of AI in engineering SDLC - English proficiency at B2 level or higher Nice to have - Proficiency in database development including SQL, PL/SQL, PostgreSQL and Azure SQL We offer - Top tech minds driving innovation in AI, cloud and digital platform modernization - Supportive team and agile, startup-like culture - Hybrid by design mode and opportunity to work remotely within Poland - Chance to work abroad for up to 60 days annually - Business-driven relocation opportunities - Career development programs - Thought leadership, mentoring, soft skills and well-being programs - Certification opportunities in Anthropic, Gemini, GCP, Azure and AWS - English classes - Stable pay - Participation in the Employee Stock Purchase Plan with a 15% discount - Benefits package including health insurance, multisport and shopping vouchers - Referral bonuses up to $2,000 - Offices featuring entertainment and relaxation zones, table tennis and football, free snacks, coffee and more - Corporate, social and well-being events Please note: - Benefits listed above are available to employees only - Terms of B2B cooperation agreements are agreed individually - Only selected candidates will be contacted

🏢 Summary: Software Engineer on the AI Data team responsible for building and scaling data collection and ingestion infrastructure to support large-scale model training. The role focuses on sourcing audio data, operating cloud-based pipelines on GCP, and collaborating with scientists to optimize cost, throughput, and quality. You will help power next-generation AI models by delivering high-quality datasets at petabyte scale. 🗂️ Requirements: BS/MS/PhD in Computer Science or related field, 5+ years of industry experience in software development, Proficiency in Bash and Python scripting, Experience working in Linux environments, Proficiency in Docker, Experience with Infrastructure-as-Code, Professional experience with at least one major cloud provider (GCP preferred), Ability to manage multiple tasks and changing priorities, Strong written and verbal communication skills 📃 Skills: Python, Bash, Linux, Docker, Terraform, GCP, Infrastructure-as-Code, Web, Crawlers, Data, Processing, Cloud 🏢 Description: Overview We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us. What You'll Do - Be scrappy to find new sources of audio data and bring it into our ingestion pipeline - Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform - Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models - Collaborate with others on the AI Team and Leadership to craft the dataset roadmap to power next-generation consumer and enterprise products An Ideal Candidate Should Have - BS/MS/PhD in Computer Science or a related field - 5+ years of industry experience in software development - Proficiency with Bash/Python scripting in Linux environments - Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (GCP) - Experience with web crawlers and large-scale data processing workflows is a plus - Ability to handle multiple tasks and adapt to changing priorities - Strong communication skills, both written and verbal What We Offer - A fast-growing environment where you can help shape the company and product - An entrepreneurial-minded team that supports risk, intuition, and hustle - A hands-off management approach so you can focus and do your best work - An opportunity to make a big impact in a transformative industry - Competitive salary, bonus, and equity depending on experience - Opportunity to work on a product used by millions of people - Work in the intersection of artificial intelligence and audio