Data Engineer - Databricks

Atos is hiring a Data Engineer - Databricks. Level rates it ; you can apply on Atos.

Level's read on this job

Works on AI ●●●○ is how Level rates this data engineer role: the daily work is on AI products, without building the model.
The posting mentions MLflow and Databricks among its tools and skills.
Level classes it as a senior role.
Atos has 609 other open roles on Level.

AI in this role

mlflowdatabricks

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.

How we rate this

Data Engineer - Databricks at Atos rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer - Databricks is an open job at Atos.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Timisoara.
The job was posted on September 27, 2026.
Seniority: senior.
Applications are handled by Atos. Apply on Atos

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

MLflowDatabricks

Also common in data engineer jobs at this level

Machine learning Airflow Snowflake Generative AI Java LLM

Pay

Typical data engineer job: $150k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

What's a project where you used MLflow hands-on?
Walk me through how you've used Databricks in your day-to-day work.
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: MLflow and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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