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Posted 2w ago

Data Engineer - Databricks

@ Atos
Timisoara, Timiș County, Romania
OnsiteFull Time
Responsibilities:designing pipelines, optimizing performance, mentoring engineers
Requirements Summary:5+ years data engineering experience with 3+ years on Databricks; strong Spark (PySpark/Scala), Python, SQL, Delta Lake, Unity Catalog, CI/CD, cloud data architecture and performance tuning skills.
Technical Tools Mentioned:Databricks, Delta Lake, Databricks Workflows, Delta Live Tables (DLT), Unity Catalog, Spark, PySpark, Scala, Python, MLflow, Databricks SQL Warehouses, Databricks Asset Bundles, Repos, Git, Azure DevOps, GitHub Actions, GitLab CI, Azure, AWS, GCP, Terraform, Structured Streaming, Kafka, Event Hubs, Kinesis, dbt, Monte Carlo, Great Expectations
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Data Engineer - Databricks

Publication Date: 
Jul 2, 2026
Ref. No: 
523741
Location: 

Timisoara, RO






Who we are.

We are a team of passionate experts with a clear ambition: applying digital technology to advance what matters for our clients and society.

Together we create reliable and responsive digital foundations for the world’s businesses, institutions, and communities.

 

With 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.

 

Learn more on Advancing what matters

 

 

We are looking for a Data 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.

This 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.

 

Key Responsibilities

  • Design, build, and optimize scalable ETL/ELT pipelines on Databricks, processing large volumes of structured and unstructured data
  • Architect and maintain Delta Lake-based data models, ensuring data quality, reliability, and performance across Bronze/Silver/Gold layers
  • Develop and orchestrate workflows using Databricks Workflows, Delta Live Tables (DLT), and job scheduling tools
  • Implement data governance, access control, and lineage using Unity Catalog
  • Optimize Spark jobs for performance and cost (cluster sizing, partitioning, caching, Photon, Z-ordering, file compaction)
  • Build and maintain CI/CD pipelines for Databricks notebooks/jobs (Databricks Asset Bundles, Repos, Git integration)
  • Collaborate with Data Scientists and ML Engineers to support feature engineering and MLflow-based model lifecycle workflows
  • Define and enforce data engineering best practices: testing, version control, observability, and documentation
  • Monitor pipeline health and cost, implementing alerting and proactive optimization (cluster policies, job clusters vs. all-purpose clusters)
  • Mentor mid-level engineers and contribute to technical decision-making and platform roadmap
  • Ensure compliance with data security and privacy requirements (e.g., GDPR)
 

Must-Have Skills

  • 5+ years of experience in Data Engineering, with 3+ years hands-on with Databricks
  • Strong proficiency in Apache Spark (PySpark and/or Scala)
  • Solid experience with Delta Lake architecture (Bronze/Silver/Gold, ACID transactions, schema evolution)
  • Hands-on experience with Unity Catalog for governance and access management
  • Strong SQL skills and experience with Databricks SQL Warehouses
  • Experience building and orchestrating pipelines with Delta Live Tables and/or Databricks Workflows
  • Proficiency in Python
  • Experience with CI/CD for data pipelines (Databricks Asset Bundles, Git, Azure DevOps/GitHub Actions/GitLab CI)
  • Strong understanding of cloud data architecture (any of Azure, AWS, or GCP)
  • Experience with performance tuning and cost optimization on Databricks clusters

 

Nice-to-Have Skills

  • Cloud-specific Databricks experience: Azure Databricks, Databricks on AWS, or Databricks on GCP
  • Experience with MLflow for experiment tracking and model registry
  • Familiarity with Terraform for infrastructure-as-code (Databricks provider)
  • Exposure to streaming data pipelines (Structured Streaming, Kafka, Event Hubs/Kinesis)
  • Experience with dbt on Databricks
  • Knowledge of data observability tools (e.g., Monte Carlo, Great Expectations)
  • Familiarity with LLMOps/AI workloads on Databricks (Vector Search, Model Serving)
  • Databricks certifications (Data Engineer Professional/Associate, Spark Developer)
  • Experience working under compliance frameworks (GDPR, ISO 27001, DORA)

 

Learn more about us:

 

At 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.

 

Whether 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. Learn more here.