Product Architect

🏢 Summary: Senior Full-Stack Developer role focused on architecting, designing, and delivering high-performance Java-based solutions for a scalable analytical platform. The position involves building core components, improving performance and non-functional aspects, and supporting back-end engineering initiatives. The role requires hands-on development across both back-end and front-end technologies. 🗂️ Requirements: 7+ years of professional software development experience, Fluency in Java and Spring, Strong knowledge of SQL and SQL databases, Experience with TypeScript and Angular, Experience building RESTful web services, Familiarity with Redis, Familiarity with ActiveMQ Artemis (JMS), Experience with Docker 📃 Skills: Java, Spring, SQL, TypeScript, Angular, Redis, ActiveMQ, Artemis, Docker, REST, JMS 🏢 Description: DataWalk is a high-tech software product company that brings the next level of technology to the world through a patent-based hybrid graph analytical platform. Our system is used by US Departments, Intelligence Agencies, and top Fortune500 companies to combat money laundering, fraud, human trafficking, terrorism or organized crime. If you are interested in making the world a safer place and leverage a unique business opportunity, please read further. We are looking for an experienced Senior Full-Stack Developer to join our Product Engineering teams. The position will play a significant role in architecting, designing, developing, and delivering high-performance Java-based software solutions that underpin our platform's stability, scalability, and efficiency. Responsibilities: Design and implement core components of the DataWalk platform. Identify, recommend, design and implement non-functional and performance improvements. Evaluate new technologies and their application to the business. Work with team members to conduct root cause analysis of issues, review code and/or design proper testing mechanisms. Support back-end engineering efficiency initiatives. Requirements: 7+ years of professional experience, preferably in a product-focused company. Fluency in Java, Spring, and SQL. Experience with TypeScript and Angular. Strong knowledge of SQL databases (preferably columnar databases) and experience with RESTful web services. Familiarity with Redis, ActiveMQ Artemis (JMS), and Docker. B2 English proficiency (for effective communication). Demonstrated high level of ownership and initiative (high agency). Ability to manage multiple priorities in a fast-paced environment. Excellent communication and collaboration skills. Nice to have: Kubernetes and Kubernetes API. Knowledge of/experience in graph analytics. Experience in the area of back-end performance measurement, analysis and improvements. We offer: Work in a high tech company with Polish-American work culture and an excellent development perspective. Work on a product based on a unique technology. Growth opportunities in a passionate team of professionals. Challenging and inspiring environment. Friendly atmosphere and attractive package of benefits (private healthcare, life insurance, multisport cards, training).

🏢 Summary: Senior Performance Test Engineer role focused on ensuring high performance and scalability of a BigData analytical platform processing terabyte-to-petabyte scale data. The position involves designing complex performance test scenarios, optimizing infrastructure and application layers, and managing Kubernetes-based test environments. You will also develop CI/CD pipelines and drive AI-assisted, proactive performance engineering practices. 🗂️ Requirements: 5+ years of performance engineering experience, Experience designing complex performance test scenarios, Hands-on experience with JMeter, Locust or k6, Experience building and maintaining CI/CD pipelines, Proficiency in Python scripting, Experience with Kubernetes administration and debugging, Experience with observability tools, Experience with BigData workloads, Experience using AI tools for automation, Polish (native), English (proficient) 📃 Skills: JMeter, Locust, k6, Jenkins, Groovy, Python, Kubernetes, OKE, EKS, CI/CD, BigData, AI, Monitoring, Logging, Tracing 🏢 Description: DataWalk is a high-tech software product company that brings the next level of technology to the world through a patent-based hybrid graph analytical platform. Our system is used by US Departments, Intelligence Agencies, and top Fortune500 companies to combat money laundering, fraud, human trafficking, terrorism or organized crime. If you are interested in making the world a safer place and leverage a unique business opportunity, please read further. We are looking for an experienced Senior Performance Test Engineer to join our Product Engineering Team. As a Senior Performance Test Engineer at DataWalk, you will be ensuring our platform delivers optimal performance at massive scale for top Fortune500 companies and other major organizations processing hundreds of billions of objects and terabytes to petabytes of data. This role demands extraordinary analytical and technical expertise to proactively discover optimal system configurations, design and maintain complex performance test scenarios, tune infrastructure and application layers, and manage test environments on Kubernetes. You will maintain CI/CD pipelines powering our performance testing process and drive the adoption of AI-assisted scripting practices to elevate our testing productivity. We foster a culture of continuous growth, encouraging you to explore and implement new tools and practices, shifting the team's focus from reactive test execution to proactive performance optimization across the entire product. This is a chance to be a part of a company that's challenging the status quo in data analysis, offering a demanding but stimulating and rewarding environment for passionate performance engineering professionals. Responsibilities: Design, develop, and maintain complex performance test scenarios for a BigData platform processing hundreds of billions of objects at terabyte-to-petabyte scale. Analyze test results, identify bottlenecks, and recommend tuning strategies for infrastructure and application layers. Develop and maintain CI/CD pipelines for performance testing (Jenkins, Groovy). Drive performance enablement across the entire Product Engineering. Manage test environments on Kubernetes clusters (OKE, EKS). Document findings, provide recommendations, and communicate results to stakeholders. Requirements: Have 5+ years of experience in performance engineering (preferably in a product company). Have hands-on experience designing and maintaining complex performance test scenarios using tools such as JMeter, Locust, k6. Have experience building and maintaining CI/CD pipelines (Jenkins, Groovy). Are proficient in Python for performance test scripting. Have practical experience in utilizing AI tools to automate and accelerate your work. Have practical experience with Kubernetes (debugging, resource management). Have experience with observability tools (monitoring, logging, tracing). Worked with BigData workloads. Have strong analytical skills, ability to work independently, take initiative, and drive improvements proactively. Native in Polish, and proficient in English. We offer: Direct impact on the global expansion of the fast growing investigative analytics company with global ambitions. A competitive salary and an attractive package of benefits (private healthcare, life insurance, multisport cards, training). Growth opportunities in a dedicated and passionate team of professionals. A challenging and inspiring environment. Work remotely in a flexible, independent work environment.

🏢 Summary: Senior Technical Expert role focused on evolving a Data Marketplace built on Data Mesh principles from a modular monolith to a microservices architecture. The position involves hands-on development in Java 21, integration of AI-driven search capabilities, and design of scalable AWS infrastructure. The goal is to deliver a seamless, e-commerce-like experience for accessing and managing digital data assets. 🗂️ Requirements: Strong experience with Java 21+, Experience with Spring Boot 3.x, Hands-on experience with messaging technologies (Solace preferred), Experience with Angular and TypeScript in SPA architecture, Knowledge of microservices and modular monolith architecture, Understanding of Data Mesh and Domain-Driven Design, Experience with PostgreSQL and MongoDB, Experience with search platforms (e.g. Sinequa), Practical experience with AWS (EC2, RDS, Lambda, EKS), Experience with Infrastructure as Code (Terraform), Knowledge of integration patterns and enterprise networking 📃 Skills: Java, Spring, Solace, Angular, TypeScript, PostgreSQL, MongoDB, Sinequa, AWS, EC2, RDS, Lambda, EKS, Terraform, Microservices, DataMesh, DDD, CI/CD 🏢 Description: As a Senior Technical Expert, you will be the technical cornerstone of our Data Marketplace —a platform built on Data Mesh principles. You will guide the evolution of a "shop-for-data" experience, moving our architecture from a robust Modular Monolith to a distributed Microservices ecosystem. You’ll be working with a cutting-edge stack (Java 21, AWS, AI-enhanced search) to ensure that "buying" digital assets is as seamless for our users as a consumer e-commerce experience. The end-goal is to build a comprehensive solution that enables FAIR data access to Digital Assets across the organization. Key Responsibilities Architectural Evolution: Lead the strategic transition from a modular monolith to microservices, ensuring domain boundaries are respected and performance remains high. Take ownership of the development of new components and ideas as you cooperate with a multidisciplinary team to deliver end-to-end experiences to the End Users. Lead Development: Write clean, high-performance code using Java 21+ features (Virtual Threads, Pattern Matching) to handle complex data transactions. Search & AI Innovation: Work on the roadmap to integrate AI/LLM capabilities into our search engine ( Sinequa ), enabling users to explore data assets via natural language and intelligent discovery. Data Stewardship: Oversee the polyglot persistence layer, optimizing PostgreSQL for relational integrity and MongoDB for flexible metadata storage. Cloud Leadership: Design and maintain scalable infrastructure within AWS , ensuring our CI/CD pipelines and deployment strategies are best-in-class. Mentorship: Act as a force-multiplier for the team, conducting rigorous code reviews and setting the standard for technical excellence. Requirements Technical Requirements Strong experience with modern Java (21+) and Spring Boot 3.x Hands-on experience with messaging technologies, ideally Solace Good understanding of SPA architecture and frontend development with Angular and TypeScript Familiarity with integration patterns and enterprise networking Solid architectural knowledge, including modular monoliths, microservices, Data Mesh, and Domain-Driven Design Experience working with PostgreSQL, MongoDB, and search platforms such as Sinequa Practical experience with AWS services, including EC2, RDS, Lambda, and EKS Experience with Infrastructure as Code, preferably Terraform Who You Are A Technical Visionary: You don't just solve today's bugs; you anticipate where the architecture will break two years from now. Data-Centric: You understand that in a Data Mesh, the product is the data itself. You care about metadata, lineage, and discoverability. User-Centered: You care about the end users experience and can cooperate with UX and Frontend developers to map and deliver first-in-class solutions. Pragmatic Architect: You know when to stick with a monolith for speed and exactly when the "swell" justifies a move to microservices. AI Curious: You are excited about moving beyond keyword search into the realm of semantic search and AI-driven data exploration. The Roadmap: What You’ll Build Phase 1: Refine the modular boundaries of the current Java 21 application. Deliver scalable and extensible transaction modules enabling Request-to-Use processes within the DataMarketPlace Phase 2: Orchestrate the "Great Migration"—consolidate existing Marketplace ecosystems into DataMarketPlace on-boarding tens of thousands of assets and thousands of users. Phase 3: Integrate AI-driven exploration features atop our Sinequa search layer. Salary: 22 000 - 33000 PLN + VAT (B2B)

🏢 Summary: Strategic Technical Product Manager (Data & AI) role owning the roadmap for customer-facing AI/ML models and data products in a SaaS environment. You will partner with executive clients to co-develop predictive features, translate business problems into technical specifications, and launch high-impact analytics solutions. This role sits at the intersection of data science, engineering, and go-to-market execution, driving measurable ARR growth. 🗂️ Requirements: 3+ years experience in Product Management, Data Analytics, or Data Engineering, Strong SQL skills (joins, aggregations), Experience with modern BI platforms (Sigma, Tableau, or Looker), Ability to translate business problems into technical data requirements, Experience working with AI/ML models or advanced analytics features, Strong understanding of SaaS product metrics and customer ROI 📃 Skills: SQL, Sigma, Tableau, Looker, Snowflake, DBT, Fivetran, Python, R, AI, ML, SaaS, Analytics, Data, Visualization 🏢 Description: We aren’t just looking for someone to manage a backlog; we’re looking for the founding architect of our customer-facing data and AI strategy. As a Technical Product Manager (Data & AI), you will sit at the intersection of Data Science, Engineering, and customer-facing value. This is a highly visible, strategic role where you’ll partner directly with executive-level clients to co-develop predictive models, analytical features, and SaaS data products. WHAT YOU'LL DO Shape the AI & Data Vision - Own the predictive roadmap for external AI/ML models, advanced analytics features, and data products - Co-innovate with strategic customers and design partners to validate ideas and uncover user needs - Partner with UX and Data Science to translate complex algorithms into intuitive data visualizations and impactful demos Execute & Ship with Impact - Translate customer business problems into technical specifications, transformation logic, and data requirements - Collaborate with Product Marketing and Sales to launch features that drive adoption, retention, and ARR expansion - Use data analysis to validate assumptions and test product hypotheses before development WHAT YOU’LL BRING - 3+ years of experience in Product Management, Data Analytics, or Data Engineering - Strong business and product acumen with ability to connect technical features to customer ROI - SQL fluency, including writing joins and aggregations - Experience with modern BI platforms such as Sigma, Tableau, or Looker - Ability to communicate effectively with executive clients, sales teams, engineers, and data scientists NICE TO HAVE - Experience with modern data stack tools such as Snowflake, DBT, Fivetran, and Sigma - Familiarity with Python or R for lightweight data analysis - Exposure to machine learning lifecycle or productionized models - Experience in complex B2B SaaS industries BENEFITS - Health and dental insurance - 401k with company match - Flexible Time Off or generous PTO plan - Paid holidays and up to 4 weeks paid bonding leave - Tuition reimbursement - Employee Assistance Program - 24/7 virtual medical care access

🏢 Summary: Lead Data Engineer role focused on driving architecture and leading a team to build scalable, secure ETL/ELT pipelines and analytics-ready data models on modern cloud platforms. The position combines hands-on engineering with technical leadership, ensuring high standards in governance, observability, and performance optimisation. You will shape data infrastructure that supports large-scale analytics across the organisation. 🗂️ Requirements: Proven experience leading data engineering or analytics engineering teams, Strong programming skills in SQL, Strong programming skills in Python, Hands-on experience with Airflow or Prefect in production, Deep practical experience with dbt, Experience with Snowflake or Databricks at scale, Strong knowledge of dimensional modelling and SCD strategies, Experience implementing data quality and governance frameworks, Experience with CI/CD and automated testing in data systems 📃 Skills: SQL, Python, Airflow, Prefect, dbt, Snowflake, Databricks, ETL, ELT, CI/CD, SCD, Dimensional, Git, IaC 🏢 Description: ABOUT THE COMPANY Our client is 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 infrastructure you lead will have real consequence across the organisation. ABOUT THE ROLE We're looking for a Lead Data Engineer to combine deep technical expertise with hands-on team leadership, guiding a team of data engineers building and maintaining ETL/ELT pipelines, data models, and governance frameworks that power analytics and reporting across the organisation. This is a technical leadership role — you'll drive architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable data solutions. You'll collaborate closely with stakeholders to align technical work with business objectives, champion governance and observability standards, and foster a culture of continuous improvement. The expectation is that you're equally effective in an architecture review as you are pairing with an engineer on a tricky pipeline problem. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data engineers, promoting collaboration, knowledge sharing, and professional growth. Set the standard for engineering quality and hold the bar consistently. Architecture and pipeline design Drive architectural decisions for ETL/ELT pipelines, orchestration frameworks (Airflow/Prefect), and transformation layers (dbt). Facilitate architecture reviews and contribute to design decisions for scalable, fault-tolerant systems. Analytics data modelling Oversee design and implementation of analytics-ready data models — dimensional schemas, SCD strategies, and semantic layers — that internal teams can build on reliably. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work. Platform optimisation Manage performance tuning and cost optimisation for Snowflake, Databricks, and related cloud data platforms at scale. Governance and observability Champion governance, observability, and compliance frameworks across all data workflows — including data quality, lineage tracking, and multi-tenant environment controls. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure timely delivery aligned with business objectives. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or analytics-focused development teams — mentoring engineers, driving architectural decisions, and owning delivery outcomes. SQL and Python Strong programming skills in both SQL and Python, applied to production data systems at scale. ETL/ELT orchestration Hands-on experience with orchestration tools — Airflow and/or Prefect — in production pipeline environments. dbt expertise Deep practical experience with dbt for transformation workflows and analytics modelling, including testing, documentation, and modular project design. Snowflake and Databricks Familiarity with Snowflake and/or Databricks for large-scale data processing, including performance tuning and cost management. Data modelling principles Solid understanding of data modelling principles, incremental strategies, and schema design for analytics — dimensional modelling, SCDs, and semantic layer design. Governance and data quality Knowledge of data quality frameworks, lineage tracking, and governance in multi-tenant environments. Software engineering practices Familiarity with CI/CD, automated testing, and infrastructure-as-code practices applied to data systems. Communication and stakeholder management Strong communication skills with the ability to operate confidently across technical teams and business stakeholders. 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 270,000 – 406,000 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, hybrid 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: Software engineering role in the Data Platform team focused on building and maintaining data-driven applications, including AI-powered data access tools. The position involves developing scalable data and metadata solutions and contributing to high-impact projects across the organization. You will work across legacy and greenfield systems while leveraging modern AI-assisted development practices. 🗂️ Requirements: 3+ years of software engineering experience, Proficiency in Python, Proficiency in SQL 📃 Skills: Python, SQL, Kubernetes, Kafka, Trino, Grafana, Prometheus, CloudWatch, AWS, Copilot, Claude, Codex, AI, Cloud, Data, Metadata 🏢 Description: Join the Data Platform team to build and maintain data-driven applications, including AI-powered data access tools. Work on a mix of legacy, improved, and greenfield projects with firm-wide impact. What you’ll do: Develop and enhance solutions for data and metadata access Build reliable, scalable applications and operational processes Experiment with AI-assisted development tools and share best practices Collaborate in a distributed team, taking ownership of impactful projects What we’re looking for: 3+ years in software engineering, Python and SQL experience Experience with data systems, cloud technologies, or AI-assisted tools is a plus Product-oriented mindset, comfortable navigating ambiguity, and impact-focused Nice to have: Experience with Kubernetes, Kafka, or federated query engines (e.g., Trino) Familiarity with monitoring/observability tools like Grafana, Prometheus, CloudWatch Experience with AWS or other cloud platforms Hands-on experience with AI coding assistants (Copilot, Claude Code, Codex, etc.) Why join: High-visibility, high-impact role across the firm Shape AI-driven development and data access practices Work on cutting-edge tech in institutional finance Collaborative culture with competitive compensation

🏢 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: Lead Distributed Data Platform Engineer responsible for architecting and delivering enterprise-scale lakehouse and distributed data platforms to enable advanced analytics and reporting. The role combines hands-on technical leadership with team mentorship, driving scalable, secure, and high-performance data solutions in cloud-native environments. You will guide architectural decisions, enforce engineering best practices, and ensure platform reliability at scale. 🗂️ Requirements: Proven experience leading data engineering or platform teams, Strong programming skills in Python, Strong programming skills in SQL, Hands-on experience with Apache Spark in production, Experience with Delta Lake and/or Apache Iceberg in production, Experience designing distributed systems and lakehouse architectures, Experience building scalable data pipelines, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Experience working in cloud-native environments 📃 Skills: Python, SQL, Spark, Delta, Iceberg, dbt, Databricks, Snowflake, Kubernetes, Docker, CI/CD, Java, Scala, Rust 🏢 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 platform you lead will underpin how the entire organisation accesses and acts on its data. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As Lead Distributed Data Platform Engineer, you'll combine deep technical expertise with hands-on team leadership — guiding a team in designing and maintaining data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services at enterprise scale. You'll lead architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable solutions. The role emphasises technical leadership, governance best practices, and a culture of innovation and continuous improvement. You'll also participate in on-call rotations as part of shared team responsibility for platform reliability. WHAT YOU'LL WORK ON Team leadership and mentorship Lead and mentor a team of data platform engineers, promoting collaboration, knowledge sharing, and professional growth. Set and maintain high engineering standards across the team. Distributed systems architecture Drive architectural decisions for distributed systems and lakehouse platforms using Spark, Delta Lake, and Iceberg. Facilitate architecture reviews and contribute to design decisions for fault-tolerant, future-ready systems. Data pipeline and platform delivery Oversee design and implementation of scalable data pipelines and analytics workflows, ensuring they are reliable, performant, and maintainable at scale. Engineering best practices Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all platform engineering work. Performance and cost optimisation Manage performance tuning, scalability strategies, and cost optimisation across cloud-native environments and large-scale distributed workloads. Governance and observability Champion governance, observability, and compliance frameworks across all data platforms — ensuring data remains accessible, secure, and auditable. Stakeholder communication Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure delivery aligns with business objectives and analytics needs. WHAT WE LOOK FOR Proven technical team leadership Demonstrated experience leading data engineering or platform development teams — mentoring engineers, owning architectural decisions, and driving delivery outcomes. Python and SQL Strong programming skills in both Python and SQL applied to production data platform work at scale. Apache Spark Hands-on experience with Spark for distributed data processing, including performance tuning and optimisation in production environments. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the trade-offs and have applied these technologies in production at scale. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and large-scale data processing. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data platform systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Communication and stakeholder management Strong communication skills with the confidence to operate across engineering teams, cross-functional partners, and senior leadership. Bonus Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. Exposure to service mesh and advanced orchestration patterns. 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 270,000 – 406,000 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.