Data Platform Solution Architect

🏢 Summary: The offer is for a Cloud Platform Architect responsible for designing and operating scalable, secure AWS-based cloud platforms. The role focuses on infrastructure as code, security, monitoring, and cost optimization while collaborating with cross-functional teams and advising clients on architecture and data strategies. It combines hands-on engineering with consulting and client-facing responsibilities. 🗂️ Requirements: Bachelor’s or Master’s degree in Computer Science, Engineering, IT or related field, Very good knowledge of English and Polish, Experience designing and operating scalable cloud platforms on AWS, Strong knowledge of cloud infrastructure, networking, and security, Hands-on experience with Infrastructure as Code tools, Experience with monitoring and cost optimization in AWS, Availability to work in hybrid mode with at least 2 office visits per month 📃 Skills: AWS, Terraform, CloudFormation, CDK, IAM, Networking, Security, Monitoring, Automation, Cloud 🏢 Description: Responsibilities Cloud Platform Architecture : Design and implement scalable, reliable cloud infrastructure on AWS. Infrastructure as Code Development : Build and maintain infrastructure automation using Terraform, CloudFormation, or CDK. Ensure infrastructure is version-controlled, reusable, and follows best practices. Security and Compliance Implementation : Design, implement, and maintain security controls, IAM policies, and network architectures ensuring compliance requirements are met and platforms remain secure. Monitoring and Operational Excellence : Establish observability frameworks, monitoring systems, and alerting mechanisms. Optimize cloud costs and address any issues that may affect platform reliability or performance. Cross-Team Collaboration and Enablement : Work closely with data, application, and DevOps teams to understand requirements and provide platform capabilities. Enable teams through documentation, tooling, and shared services Consulting and Strategy : Provide expert advice and consultancy services to clients on data strategies, architecture choices, and technological advancements Client Interaction : Work closely with clients to understand their business needs and technical requirements. Translate these requirements into effective data engineering solutions. Benefits Motivizer Benefits Platform to choose and manage all your benefits in one place. You receive a budget (550 PLN monthly). You can choose medical care package, meal tickets, sports cards (we have Multisport and on preferential terms, we have membership cards to one of the most popular Gyms), cinema tickets, shop vouchers, discounts and many more. Language Courses – you'll have access to a multi-language learning platform enabling you to practice you language skills and learn new ones! Regular and systematic further training opportunities - both internally and from external providers. We support your ongoing learning and development. Cooperation within an internal community is our everyday reality. We have networking events, coding challenges, and company parties for different occasions. Qualifications Educational Background: Bachelor’s or master’s degree in CS, Engineering, IT, or a related field. Very good knowledge of English and Polish. Experience designing and operating scalable, reliable cloud platforms on AWS. Strong background in cloud infrastructure, networking, and security for shared platform environments. Hands-on experience with Infrastructure as Code (Terraform, CloudFormation, CDK) and automation. Experience with monitoring, cost optimization, and operational excellence in AWS. Availability to work in a hybrid mode with at least 2 visits to the office per month. About Data Reply Data Reply, as part of the Reply Group, offers a wide range of services to help customers to become data driven. The team is active in various industries and business areas and works closely with clients to enable them to achieve meaningful results through the effective use of data. Data Reply offers many years of experience in transformation projects on the topic of "Data Driven Enterprise". Our experts focus on the development of Streaming and Event-Driven applications, Data Platforms and Machine Learning solutions - automated, efficient and scalable - without compromising IT security.

🏢 Summary: Hands-on .NET Architect role focused on designing and guiding delivery of secure, scalable, cloud-native enterprise platforms on Azure. The position combines deep technical expertise in C# and distributed systems with ownership of target architecture and production-grade solution design. Emphasis on microservices, platform engineering, data architecture, security, and DevSecOps practices. 🗂️ Requirements: Degree in Computer Science or related field, 10+ years in software engineering or solution architecture on Microsoft stack, Strong expertise in C# and .NET Core/.NET 8, Experience with ASP.NET Core and Web APIs, Architecture of distributed systems and microservices, Azure architecture across AKS and core Azure services, Design of integration-heavy enterprise platforms, Strong knowledge of SQL Server or PostgreSQL performance tuning, Understanding of scalability, availability, and resiliency patterns, Experience with containers, Kubernetes, and CI/CD, Knowledge of application security and secure coding practices, Foundational understanding of AI and machine learning concepts 📃 Skills: C#, .NET, ASP.NET, Azure, AKS, Microservices, APIs, SQL, SQLServer, PostgreSQL, Kubernetes, Docker, CI/CD, DevSecOps, ServiceBus, EventGrid, KeyVault, AppServices, Functions, APIManagement, Storage, Authentication, Encryption, Datadog, Dynatrace, ApplicationInsights, OpenTelemetry, Grafana, AI 🏢 Description: Description We are seeking a forward-looking, hands-on .NET Architect who can shape the target architecture for modern platforms while staying close to engineering delivery. The ideal candidate will combine deep expertise in C#, .NET, Azure, cloud-native architecture, distributed systems, APIs, data, and platform engineering with the ability to guide teams through practical, production-grade solution design. This role is suited to an architect who can think 3–5 years ahead, simplify complex landscapes, and help build secure, scalable, resilient, and configurable enterprise platforms. Requirements Bachelor’s or master’s degree in Computer Science, Engineering, or a related field 10+ years of experience in software engineering, solution architecture, or platform engineering, with significant experience in Microsoft technology stacks Strong hands-on expertise in C#, .NET / .NET Core / .NET 8, ASP.NET Core, Web APIs, background services, and enterprise application design Deep experience in architecting distributed systems using microservices, asynchronous messaging, event-driven design, and API-led integration patterns Strong Azure architecture experience, preferably across AKS, App Services, Functions, API Management, Key Vault, Service Bus, Event Grid, Storage, monitoring, and identity integration patterns Experience designing and supporting platforms, configurable product architectures, and integration-heavy enterprise solutions Strong understanding of relational databases and performance engineering, especially SQL Server and/or PostgreSQL, including schema design, indexing, query tuning, and transaction handling Solid grasp of non-functional architecture including performance, scalability, availability, fault isolation, observability, and disaster recovery Strong understanding of application and platform security including authentication, authorization, secrets management, encryption, secure coding, and compliance-oriented design Experience with containers, Kubernetes, CI/CD, infrastructure automation, and modern DevSecOps practices Ability to make sound architecture decisions with a balance of pragmatism, delivery speed, engineering quality, and long-term maintainability Strong communication and stakeholder management skills across product, engineering, architecture, operations, security, and client-facing teams Foundational understanding of AI concepts, including how machine learning models  work, common AI use cases, and basic principles of data handling. Ability to use AI‑powered tools and platforms to support daily tasks, with strong attention to detail and commitment to maintaining data accuracy. Fluent command of the Polish language (C1/C2) Desirable Qualifications and Skills Experience in insurance, Insurtech, BFSI, or other regulated, transaction-heavy domains. Exposure to policy administration, billing, accounting, claims, workflow orchestration, or reporting platforms within the insurance value chain. Experience with architecture frameworks and modeling approaches such as TOGAF, domain-driven design, UML, C4, or equivalent practical architecture methods. Familiarity with mixed technology landscapes involving .NET, Java/Spring Boot, enterprise workflow tools, and integration ecosystems. Experience with observability and reliability tooling such as Datadog, Dynatrace, Application Insights, Open Telemetry, Grafana, or similar. Working knowledge of Angular, React, or modern web application architecture patterns. Exposure to AI-enabled engineering, intelligent automation, or embedding AI capabilities into enterprise platforms. Leadership experience across globally distributed or virtual teams. What you can expect from us: Unique professional and personal development at one of the pioneer companies in professional insurance support. Ongoing professional training – to onboard you for a good start and your further professional development. Your own growth training budget - use internal and external development opportunities and take advantage of your own budget. LUXMED medical cover for you with full dental care, oncological preventive program and additional mental health support with helpline & individual sessions with a therapist.. 8-hour work time with a lunch break already included - spend the rest of the day doing what is important to you as intended in the #2h4Family program. Private life insurance - 80% of the premium is covered by an employer. Employee referral program - we appreciate you recommending your friends to join us. Additional days off - to celebrate your birthday, moreover, if you want to do a volunteering work, feel free to do so with some extra days off. Integration events - monthly delicious breakfasts, movie nights, board game nights, outdoor events. Lively and modern office in the City Centre with parking space for employees. A supportive and friendly atmosphere created by passionate people.

🏢 Summary: The offer is for a Data Architect responsible for designing and developing a modern data architecture and Data Platform supporting strategic business goals. The role focuses on building and maintaining data warehouses, Data Lake/Lakehouse ecosystems, metadata management, and large-scale data integration across on-premise and cloud environments. The position combines architectural design, data governance, and collaboration with analytics and business teams. 🗂️ Requirements: Minimum 5 years of experience in data domain, Minimum 2 years of experience as Data Architect or equivalent, Experience in designing data warehouses or data platforms, Knowledge of relational and dimensional data modeling, Experience with data modeling tools, Experience in metadata management and data cataloging, Proficiency in SQL, Experience with data processing languages, Experience in large-scale data integration, Experience with ETL/ELT tools, Knowledge of Data Governance and Data Quality principles, Experience with cloud platforms in data processing context 📃 Skills: SQL, Python, Oracle, Teradata, Snowflake, BigQuery, Redshift, Erwin, PowerDesigner, IBMDataArchitect, Informatica, AbInitio, DataStage, Talend, dbt, Airbyte, AWS, Azure, GCP, DataLake, Lakehouse, DataGovernance, RODO 🏢 Description: Opis stanowiska Architekt Danych będzie odpowiedzialny za projektowanie i rozwój nowoczesnej architektury danych, w tym nowoczesnej Platformy Danych wspierającej strategiczne cele firmy. Poszukujemy eksperta, który potrafi łączyć wiedzę techniczną ze rozumieniem potrzeb biznesowych, zapewniając wymaganą jakość i dostępność danych w całej organizacji. Jeśli masz doświadczenie w budowaniu hurtowni danych, rozwiązań BI, integracji źródeł danych (on-premise, chmura) – ta rola jest dla Ciebie. Główne obowiązki Projektowanie, rozwój i utrzymanie spójnej architektury danych dla systemów wewnętrznych oraz zewnętrznych (w tym ekosystemu Data Lake/Lakehouse, hurtowni danych i rozwiązań analitycznych). Dobór narzędzi i technologii do przetwarzania danych wraz z koordynacją ich wdrożenia. Projektowanie i utrzymanie Katalogu Metadanych oraz Mapy Przepływu Danych Standaryzacja modelowania danych i zarządzanie danymi słownikowymi. Powiązanie architektury danych z cyklem życia oprogramowania (SDLC). Utrzymanie katalogu źródeł danych zewnętrznych. Współpraca z zespołami analitycznymi i interesariuszami biznesowymi w celu identyfikacji wymagań dotyczących danych oraz zlecanie lub realizacja analizy biznesowej w inicjatywach jednostek Data & Analytics. Tworzenie i aktualizacja dokumentacji architektonicznej oraz mapowania procesów biznesowych na architekturę danych. Wymagania Minimum 5 lat doświadczenia w obszarze danych, w tym przynajmniej 2 lata na stanowisku Architekta Danych lub równorzędnym. Doświadczenie w projektowaniu hurtowni danych i/lub platform danych (np. Oracle, Teradata, Snowflake, BigQuery, Redshift itp.). Znajomość zagadnień modelowania danych i informacji (relacyjnego i wielowymiarowego) oraz umiejętność modelowania danych w odpowiednich narzędziach (np. Erwin, Power Designer, IBM Data Architect itp.). Doświadczenie w definiowaniu i zarządzaniu metadanymi (katalog danych, pojęcia biznesowe itp.). Biegłość w SQL oraz znajomość wybranych języków do przetwarzania danych (np. Python). Kompetencje i doświadczenie w wielkoskalowej integracji danych. Doświadczenie z narzędziami ETL/ELT (np. Informatica PC, Ab Initio, IBM Data Stage, Talend, dbt, Airbyte itp.). Znajomość zasad Data Governance, zarządzania Jakością Danych oraz retencji danych osobowych (np. RODO). Doświadczenie z chmurą (AWS, Azure lub GCP) w kontekście przetwarzania i przechowywania danych. Samodzielność i zdolność podejmowania decyzji architektonicznych. Umiejętność pracy w zespole interdyscyplinarnym (biznes, IT, data science, bezpieczeństwo). Komunikacja z interesariuszami technicznymi i biznesowymi. Zainteresowanie nowoczesnymi trendami w inżynierii danych (np. Data Mesh, Data Fabric, Lakehouse, streaming danych, active metadata itp.). Oferujemy Zaawansowany stack technologiczny i ciekawe projekty. Współpracę hybrydową (ze zdalną 6 dni w miesiącu) z energicznym i profesjonalnym zespołem. Możliwość rozwoju w ramach firmy - regularne szkolenia techniczne. Prywatna opieka medyczna, ubezpieczenie na życie i karta sportowa. Nagrody roczne oraz jubileuszowe.

🏢 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.

🏢 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: Remote Platform Engineer role focused on designing, building, and operating enterprise-grade Azure data platforms for BI and analytics teams. The position centers on Infrastructure as Code, CI/CD automation, Databricks platform management, and secure cloud architecture. The engineer acts as a platform advisor, ensuring reliability, security, and scalability of Azure-based data solutions. 🗂️ Requirements: Strong admin-level experience with Microsoft Azure, Experience with Entra ID / Azure AD and RBAC, Hands-on experience with Azure networking, ADLS Gen2, Key Vault, Commercial experience with Terraform in modular, multi-environment setups, Hands-on CI/CD using Azure DevOps, GitHub Actions or GitLab, Practical platform experience with Databricks (clusters, jobs, governance), Platform/SRE mindset with monitoring and incident management, Scripting skills in PowerShell or Python, Experience with enterprise cloud architectures, English and Polish proficiency, Power BI experience 📃 Skills: Azure, EntraID, AzureAD, RBAC, Networking, ADLSGen2, KeyVault, Terraform, CICD, AzureDevOps, GitHubActions, GitLab, Databricks, AzureMonitor, LogAnalytics, PowerShell, Python, PowerBI 🏢 Description: In Cyclad we work with top international IT companies in order to boost their potential in delivering outstanding, cutting-edge technologies that shape the world of the future. We are seeking an experienced Platform Engineer to join our client, an IT company specializing in AI consultancy. You will have a key role in designing, building, and operating enterprise-grade data platforms that enable analytics teams to deliver real business value. You will be responsible for the Azure foundation behind Business Intelligence and Data solutions — from secure networking and identity, through Infrastructure as Code, to Databricks operations and CI/CD automation. This role is ideal for someone with a strong platform/SRE mindset who enjoys building scalable cloud architectures, automating everything, and acting as a technical advisor for analytics and BI teams. Project information: Work Setup: 100% Remote work Rate: 160 – 180 PLN/net/h + VAT (B2B contract) Start date: March 2026/ depending on candidate availability Language: English (min B2+) Project scope: Design and operate enterprise Azure data platforms (identity, networking, storage, security). Build Infrastructure as Code with Terraform (modules, environments, Azure + Databricks providers). Create and maintain CI/CD pipelines (Azure DevOps / GitHub Actions / GitLab). Manage Databricks from the platform side (clusters, jobs, secrets, repos, permissions). Implement monitoring and observability (Azure Monitor / Log Analytics). Support analytics teams by ensuring stability, performance, and security. Troubleshoot production issues and drive RCA. Automate operations using PowerShell and/or Python. Act as a platform advisor for BI and data teams. Requirements: Strong admin-level experience with Microsoft Azure (Entra ID / Azure AD, RBAC, networking, ADLS Gen2, Key Vault). Commercial experience with Terraform (modular, multi-env setups). Hands-on CI/CD using Azure DevOps, GitHub Actions or GitLab. Practical platform knowledge of Databricks (clusters, jobs, governance). Platform/SRE mindset (monitoring, incidents, reliability). Scripting skills (PowerShell/Python). Experience with enterprise cloud architectures. English & Polish proficiency. Power BI background We offer: Full-time job agreement based on B2B Private medical care with dental care (covering 70% of costs) + rehabilitation package. Family package option possible Multisport card (also for an accompanying person) Life insurance

🏢 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: The role focuses on designing and building scalable, cloud-native data platforms to enable advanced analytics and reporting across a large internal data ecosystem. It involves developing distributed data pipelines, lakehouse architectures, and optimised data warehousing solutions with strong emphasis on performance, governance, and reliability. The position requires deep technical expertise in big data technologies and cloud-native infrastructure, including on-call responsibility for platform stability. 🗂️ Requirements: Strong programming skills in Python, Strong programming skills in SQL, Commercial experience with Apache Spark for distributed data processing, Hands-on experience with Delta Lake and/or Apache Iceberg in production, Experience with dbt for SQL transformations, Experience with Databricks and Snowflake, Knowledge of CI/CD and automated testing practices, Experience with Kubernetes and Docker, Understanding of performance tuning and cost optimisation in large-scale data systems, 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. Over 75% of our business has transitioned to our cloud platform, and we are 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 build will have real consequence. ABOUT THE ROLE We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As an Advanced Data Platform Engineer, you'll design and implement scalable, cloud-native data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services to support diverse analytical use cases at enterprise scale. The role emphasises technical depth — performance optimisation, governance best practices, and the kind of engineering rigour that keeps vast datasets accessible, secure, and compliant. You'll work closely with internal teams to deliver curated datasets and self-service analytics capabilities, and you'll participate in on-call rotations as part of shared team responsibility. WHAT YOU'LL WORK ON Data pipeline and distributed systems design Design and implement complex data pipelines and distributed systems using Spark and Python, applying clean code principles, modular design, CI/CD, automated testing, and thorough code reviews. Lakehouse platform development Develop and maintain lakehouse capabilities with Delta Lake and Apache Iceberg, ensuring reliability, performance, and long-term maintainability at scale. Analytics workflow enablement Integrate dbt for SQL transformations running on Spark. Deliver curated datasets and self-service analytics capabilities that empower internal stakeholders to explore data independently. Data warehousing optimisation Optimise Databricks and Snowflake environments for performance and scalability. Drive cost optimisation and performance tuning across Spark jobs and cloud-native infrastructure. Observability and governance Implement observability and governance frameworks including data lineage tracking and compliance controls, ensuring data remains secure and auditable. 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 Python and SQL — the foundation for everything you'll build here. Apache Spark Solid experience with Spark for distributed data processing at scale, including performance tuning and optimisation. Lakehouse architecture Expertise in Delta Lake and/or Apache Iceberg. You understand the tradeoffs and have used these in production environments. Analytics tooling Familiarity with dbt, Databricks, and Snowflake for analytics workflows and SQL transformation pipelines. Software engineering fundamentals Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems. Infrastructure and containerisation Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments. Scalability and cost optimisation Understanding of performance tuning, scalability strategies, and cost optimisation for large-scale 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 160,000 – 240,000 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.