{"id":2004706,"url":"https://alion.io/job/atos-data-engineer-databricks","title":"Data Engineer - Databricks","company":{"id":3006,"name":"Atos","domain":"atos.net","url":"https://alion.io/company/atos","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SuccessFactors","truth_index":null},"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":"structured","locations":["Timișoara, Romania"],"countries":["RO"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":34000,"max_usd":88000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2127},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","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":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"MLFlow","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"dbt","optional":true},{"name":"Great Expectations","optional":true},{"name":"ISO 27001","optional":true},{"name":"LLMOps","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-09-27T02:00:00Z","employer_posted_date":"2026-09-27","last_verified_at":"2026-10-11T15:52:55Z","board_verified":true,"closed_at":null,"days_open":14,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":14},"description":"Who we are.\nWe are a team of passionate experts with a clear ambition: applying digital technology to advance what matters for our clients and society.\nTogether we createreliable and responsive digital foundations for the world’s businesses, institutions, and communities.\nWith a 10 year history in Romania and over 2200 employees, Atos has a presence in 3 of the largest cities in Romania: Bucharest, Brasov and Timisoara. Our Global Delivery Center in Romania offers cutting-edge, best in class, end-to-end IT services for more than 300 clients located around the world.\nLearn more on Advancing what matters\nWe are looking for aData Engineer with deep expertise in Databricks to design, build, and scale our data platform. You will own the architecture and performance of large-scale data pipelines, drive best practices across the Lakehouse stack, and partner closely with Data Science, Analytics, and AI Engineering teams to deliver reliable, production-grade data infrastructure.\nThis role is ideal for someone who has moved beyond writing pipelines to also shaping platform standards, mentoring engineers, and making architectural decisions on a Databricks-based Lakehouse.\nKey Responsibilities\nDesign, build, and optimize scalable ETL/ELT pipelines on Databricks, processing large volumes of structured and unstructured data\nArchitect and maintain Delta Lake -based data models, ensuring data quality, reliability, and performance across Bronze/Silver/Gold layers\nDevelop and orchestrate workflows using Databricks Workflows, Delta Live Tables (DLT), and job scheduling tools\nImplement data governance, access control, and lineage using Unity Catalog\nOptimize Spark jobs for performance and cost (cluster sizing, partitioning, caching, Photon, Z-ordering, file compaction)\nBuild and maintain CI/CD pipelines for Databricks notebooks/jobs (Databricks Asset Bundles, Repos, Git integration)\nCollaborate with Data Scientists and ML Engineers to support feature engineering and MLflow -based model lifecycle workflows\nDefine and enforce data engineering best practices: testing, version control, observability, and documentation\nMonitor pipeline health and cost, implementing alerting and proactive optimization (cluster policies, job clusters vs. all-purpose clusters)\nMentor mid-level engineers and contribute to technical decision-making and platform roadmap\nEnsure compliance with data security and privacy requirements (e.g., GDPR)\nMust-Have Skills\n5+ years of experience in Data Engineering, with 3+ years hands-on with Databricks\n Databricks Technical Administration and Maintenance (SME-level: knowledge acquisition, ongoing support and maintenance of the Databricks platform) \n Skills: Databricks Platform, Data Science\nStrong proficiency in Apache Spark (PySpark and/or Scala)\nSolid experience with Delta Lake architecture (Bronze/Silver/Gold, ACID transactions, schema evolution)\nHands-on experience with Unity Catalog for governance and access management\nStrong SQL skills and experience with Databricks SQL Warehouses\nExperience building and orchestrating pipelines with Delta Live Tables and/or Databricks Workflows\nProficiency in Python\nExperience with CI/CD for data pipelines (Databricks Asset Bundles, Git, Azure DevOps/GitHub Actions/GitLab CI)\nStrong understanding of cloud data architecture (any of Azure, AWS, or GCP)\nExperience with performance tuning and cost optimization on Databricks clusters\nNice-to-Have Skills\nCloud-specific Databricks experience: Azure Databricks, Databricks on AWS, or Databricks on GCP\nExperience with MLflow for experiment tracking and model registry\nFamiliarity with Terraform for infrastructure-as-code (Databricks provider)\nExposure to streaming data pipelines (Structured Streaming, Kafka, Event Hubs/Kinesis)\nExperience with dbt on Databricks\nKnowledge of data observability tools (e.g., Monte Carlo, Great Expectations)\nFamiliarity with LLMOps/AI workloads on Databricks (Vector Search, Model Serving)\nDatabricks certifications (Data Engineer Professional/Associate, Spark Developer)\nExperience working under compliance frameworks (GDPR, ISO 27001, DORA)\nLearn more about us:\nAt Atos, we embrace diversity as the ultimate engine of ingenuity for our clients, and we constantly strive to create a culture where people feel supported and encouraged. Read more about our commitment here.\nWhether it is fighting climate change, promoting digital inclusion, or ensuring trust in data management - tech for good sits at the core of our identity. With numerous global recognitions for our ESG practices, we are committed to building a better future for all by harnessing the power of technology. 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