{"id":2543780,"url":"https://alion.io/job/euroclear-senior-data-engineeranalyst-azure-databricks","title":"Senior Data Engineer/Analyst - Azure Databricks","company":{"id":61,"name":"Euroclear","domain":"euroclear.com","url":"https://alion.io/company/euroclear","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":81,"open_postings":16,"ghost_share":0,"stale_share":0.75,"repost_share":0,"time_to_fill_p50_days":52,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Poland"],"countries":["PL"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":59000,"max_usd":98000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":107},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Machine Learning","optional":true},{"name":"Scala","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-10-14T16:19:40Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T03:11:34Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Senior Data Engineer - Azure Databricks\nJoin Euroclear\nEuroclear is a financial services company that specializes in the settlement of securities transactions, as well as the safekeeping and asset servicing of these securities. We are located in Brussels and several major cities in Europe and around the world. We are deeply convinced that diversity of talents, backgrounds and opinions is a key to success, by encouraging engagement, energy and innovation.\nOur IT Division\nThe Data & AI division ensures Euroclear's competitiveness by delivering reliable and sustainable IT solutions for the financial securities markets.\nWithin Data & AI division, our Data Tribe supports advanced analytics, reporting, operational data products, and AI-driven capabilities across the Euroclear Group. We help transform data into business value by leveraging modern cloud technologies, data engineering practices, and innovative analytical solutions.\nOur scope can be summarized as follows:\nOperating and evolving the Data & Analytics Platform (DAP), including the Data Lake, Group Data Warehouse, and strategic Azure-based data platforms.\nDelivering data products and analytics capabilities for key business domains.\nSupporting business transformation initiatives through modern data engineering and cloud technologies.\nProviding expertise in data management, reporting, analytics, and AI.\nOur tribe is working for both internal and external clients.\nYour Role as a Senior Data Engineer\nAs a Senior Data Engineer, you will play a key role in designing, building, and evolving modern cloud-based data solutions supporting Euroclear's business domains.\nYou will work closely with business stakeholders, architects, product owners, and fellow engineers to deliver scalable, reliable, and high-performing data products that support operational processes, reporting, analytics, and future AI initiatives.\nKey Responsibilities\nDesign, develop, test, and maintain scalable data engineering solutions on Microsoft Azure and Databricks.\nBuild robust and reusable ETL/ELT pipelines using Python, PySpark, and SQL.\nDevelop data products and applications supporting data ingestion, transformation, enrichment, validation, and distribution.\nImplement reliable batch and streaming data workflows using Azure Databricks, Delta Lake, and modern Lakehouse architectures.\nContribute to the modernization and migration of strategic data platforms to Azure Cloud.\nBuild and maintain datasets supporting operational, analytical, management, and regulatory reporting.\nPartner with business and technology teams to translate requirements into scalable, maintainable solutions.\nPromote engineering excellence through code quality, automation, performance optimization, and operational reliability.\nMentor and support junior engineers through coaching, code reviews, and knowledge sharing.\nAzure / Databricks Data Platform\nDevelop solutions leveraging Azure and Databricks services, including:\nAzure Databricks\nDelta Lake / Lakehouse Architecture\nAzure Data Lake Storage\nAzure Data Factory / Synapse Pipelines\nAzure Event Hubs and Streaming Ingestion Patterns\nAzure Key Vault\nAzure DevOps\nKey Responsibilities\nDesign and implement curated data layers supporting analytics, reporting, operational processes, and AI use cases.\nBuild and maintain scalable data models\nApply best practices for data quality, lineage, observability, performance optimization, and operational monitoring.\nEnsure data solutions are secure, scalable, resilient, and aligned with Enterprise Architecture standards.\nCollaborate with platform, infrastructure, and architecture teams to continuously improve the data ecosystem.\nETL, Data Pipelines & Software Engineering\nDevelop and maintain production-grade data pipelines using Python, PySpark, and SQL.\nDesign reusable ingestion, transformation, validation, and monitoring frameworks.\nImplement automated testing, validation, logging, error handling, and monitoring.\nOptimize Spark jobs for performance, scalability, reliability, and cost efficiency.\nApply software engineering best practices including clean code, modular design, version control, code reviews, and documentation.\nBuild CI/CD pipelines using Azure DevOps YAML pipelines.\nPackage, deploy, and maintain data engineering solutions across multiple environments.\nContribute to operational support activities and continuous service improvement.\nInfrastructure & DevOps Collaboration\nCollaborate with Cloud, DevOps, Platform, and Security teams to ensure operational readiness of delivered solutions.\nContribute to infrastructure automation initiatives where required.\nSupport the integration of data applications with cloud services, security controls, and deployment pipelines.\nFollow DevOps practices for release management, environment promotion, monitoring, and production support.\nContribute to the adoption of Infrastructure-as-Code principles and cloud engineering best practices.\nCollaboration & Technical Leadership\nWork closely with Business Analysts, Product Owners, Architects, Data Scientists, and Engineering teams.\nTranslate business challenges into robust and scalable data engineering solutions.\nProvide technical leadership on Databricks, Spark, Cloud Data Platforms, and Data Engineering best practices.\nContribute to architecture discussions, design standards, and reusable engineering patterns across the tribe.\nSupport and coach less experienced engineers through mentoring, knowledge sharing, and technical guidance.\nFoster a culture of continuous improvement, collaboration, and engineering excellence.\nRequired Qualifications\n5+ years of hands-on experience in data engineering, cloud data platform development, or large-scale data solutions.\nStrong hands-on development experience with:Python\nPySpark\nSQL\nETL/ELT development\nNice to have: Scala\n\nProven experience working with the Azure Databricks ecosystem, including:Databricks notebooks and jobs\nSpark clusters\nDelta Lake\nLakehouse Architecture\nPerformance tuning and optimization\n\nExperience designing, developing, and operating production-grade data pipelines.\nStrong understanding of data modelling concepts for operational and analytical platforms.\nExperience with Azure services including:Azure Data Lake Storage\nAzure Data Factory\nAzure Key Vault\nAzure DevOps\nAzure monitoring and observability solutions\n\nExperience implementing CI/CD pipelines, preferably using Azure DevOps YAML pipelines.\nStrong understanding of software engineering principles including automated testing, version control, code reviews, and modular design.\nKnowledge of cloud security, data governance, observability, and cost-aware engineering practices.\nExperience working in complex enterprise environments with multiple stakeholders and delivery teams.\nPreferred Qualifications\nExperience with large-scale distributed data processing using Apache Spark.\nExperience with streaming architectures and real-time data processing.\nExperience building reusable data engineering frameworks, libraries, and shared components.\nKnowledge of data governance, metadata management, lineage, and data quality frameworks.\nExperience supporting analytics, reporting, AI, or machine learning use cases.\nExperience contributing to cloud migration and data modernization initiatives.\nFamiliarity with Infrastructure-as-Code concepts (Terraform or equivalent).\nPreferred Certifications\nAzure Certifications\nMicrosoft Certified: Azure Data Engineer Associate\nMicrosoft Certified: Azure Developer Associate\nMicrosoft Certified: Azure Solutions Architect Expert\nMicrosoft Certified: Azure DevOps Engineer Expert\nDatabricks Certifications\nDatabricks Certified Data Engineer Associate\nDatabricks Certified Data Engineer Professional\nDatabricks Certified Developer for Apache Spark\nSoft Skills\nStrong communication and documentation skills.\nAbility to translate business requirements into practical and sustainable technical solutions.\nStrong analytical and problem-solving mindset.\nOwnership, accountability, and proactive attitude.\nTeam-oriented and comfortable working in a collaborative, cross-functional environment.\nAbility to influence technical decisions and drive continuous improvement.\nPassion for learning and adopting modern data engineering technologies and practices.\nStrong mentoring and coaching capabilities.\nWhy Join Us?\nYou will have the opportunity to work on some of Euroclear's most strategic data initiatives, helping modernize our data platforms and enabling the next generation of data, analytics, and AI capabilities that support key business domains across Settlement, Collateral, and Banking.","description_format":"text","description_chars":8602,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"region"},{"name":"France","iso":"FR","kind":"region"},{"name":"United Kingdom","iso":"GB","kind":"region"},{"name":"Austria","iso":"AT","kind":"region"},{"name":"Belgium","iso":"BE","kind":"region"},{"name":"Bulgaria","iso":"BG","kind":"region"},{"name":"Croatia","iso":"HR","kind":"region"},{"name":"Czech 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