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Data Engineer - Databricks
Timisoara, RO
Actively hiring, first seen by us 1 day ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and optimize ETL/ELT pipelines on Databricks for large data volumes
Optimize Spark jobs for performance and cost
Mentor mid-level engineers and shape the platform roadmap
From the employer’s posting
Design, build, and optimize scalable ETL/ELT pipelines on Databricks
Optimize Spark jobs for performance and cost (cluster sizing, partitioning, caching, Photon, Z-ordering, file compaction)
Mentor mid-level engineers and contribute to technical decision-making and platform roadmap
Posting record
Report an errorActively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 5, 20261 day ago
- Recorded sightings
- 2
- Last seen by us
- Nov 6, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
ATOS International is hiring
18 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Scala
- SQL
- AWS
- Azure
- Databricks
- dbt
- Delta Lake
- GCP
- Kafka
- MLflow
- Spark
- Terraform
- PySpark
Where the posting names them
- 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)
- Skills: Databricks Platform, Data Science - 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
- 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
- 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)
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.
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
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
- 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
Must-Have Skills - 5+ years of experience in Data Engineering, with 3+ years hands-on with Databricks - Databricks Technical Administration and Maintenance (SME-level: knowledge acquisition, ongoing support and maintenance of the Databricks platform)
- 5+ years of experience in Data Engineering, with 3+ years hands-on with Databricks - Databricks Technical Administration and Maintenance (SME-level: knowledge acquisition, ongoing support and maintenance of the Databricks platform) - Skills: Databricks Platform, Data Science
- Databricks Technical Administration and Maintenance (SME-level: knowledge acquisition, ongoing support and maintenance of the Databricks platform) - Skills: Databricks Platform, Data Science - Strong proficiency in Apache Spark (PySpark and/or Scala)
- 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
- 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
- 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)
- 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)
- 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)
- 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)
- 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
- 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
- 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
- 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
- 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)
- 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)
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Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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
- Databricks Technical Administration and Maintenance (SME-level: knowledge acquisition, ongoing support and maintenance of the Databricks platform)
- Skills: Databricks Platform, Data Science
- 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.
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Timisoara, RO
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