Senior Data Engineer (Databricks)

Entrada; Polska; Remote; PLN 394,000 - 525,000; Full time

Benefits offered by this job

Remote work flexibility

Databricks certifications support

Mentorship from Databricks MVPs

Professional growth and thought-lead I

Job summary

Entrada AI seeks a Senior Data Engineer to lead scalable data solutions for global clients. You will architect modern Lakehouse environments, migrate data warehouses to Lakehouse, and optimize Spark jobs while advising stakeholders on best practices.

We value a consultant mindset, strong Python/SQL skills, and experience across Azure or AWS, Unity Catalog, and Databricks Apps. Excellent English communication is essential for client engagement.

Qualifications

• 5–7+ years in Data Engineering or distributed systems.
• At least 3 years hands-on in the Databricks ecosystem (Delta Lake internals).
• Advanced proficiency in Python and SQL with production experience in Azure or AWS.
• Experience with Unity Catalog and dbt or Delta Live Tables for orchestration.
• Fluent English (C1+) for direct client collaboration.

Responsibilities

• Design and implement scalable data pipelines using Apache Spark (PySpark) on Databricks.
• Migrate legacy data warehouses to Lakehouse architecture with Delta Lake.
• Analyze and optimize Spark jobs for performance and cost (partitioning, z-ordering, Photon).
• Enforce high code quality through reviews and CI/CD (Databricks Asset Bundles) with Unity Catalog security.
• Share knowledge with the internal team and advise clients on data strategy.

Skills

Python and SQL

Databricks (Delta Lake)

Spark / PySpark

Unity Catalog

dbt or Delta Live Tables

Cloud (Azure/AWS)

Tools

Databricks

Delta Lake

Unity Catalog

dbt

Delta Live Tables

Azure Data Factory / S3

Job description

About Entrada AI

Entrada AI is a specialized consulting partner and a strategic portfolio company of Databricks Ventures. We were recently named the

About Entrada AI

Entrada AI is a specialized consulting partner and a strategic portfolio company of Databricks Ventures. We were recently named the Genie Partner of the Year (2026) for our work deploying Databricks Genie at enterprise scale—bridging the gap between AI ambition and the trusted, governed data required for accurate responses. With over 150 Databricks projects delivered, we unlock self-service analytics for Fortune 500 leaders. Databricks invested in us because of our technical excellence, placing us in the "inner circle" of the ecosystem. For our engineers, this means direct access to product roadmaps, private previews, and the teams building the platform. You will join a team of industry veterans who value clean architecture over quick fixes. We don't just maintain pipelines; we solve complex architectural challenges.

About The Role

As a Senior Data Engineer, you will lead the design and implementation of scalable data solutions for our global clients. You will move beyond simple script-running to architecting modern Lakehouse environments. This role requires a consultant’s mindset—balancing technical depth with the ability to advise stakeholders on best practices and long-term data strategy.

Key Responsibilities

• Architecture & Development: Design and implement scalable data pipelines using Apache Spark (PySpark) on Databricks.
• Modernization: Migrate legacy data warehouses to the Lakehouse architecture using Delta Lake.
• Optimization: Analyze and optimize complex Spark jobs for performance and cost (partitioning, z-ordering, Photon engine utilization).
• Standards & Governance: Enforce high code quality through rigorous code reviews and CI/CD implementation (Databricks Asset Bundles), while ensuring security via Unity Catalog.
• Technical Leadership: Share knowledge with the internal team and act as a strategic technical advisor for clients.

Requirements

• Experience: 5–7+ years in Data Engineering or distributed systems, with at least 3 years of deep, hands‑on experience specifically within the Databricks ecosystem (including Delta Lake internals).
• Cloud & Engineering: Advanced proficiency in Python and SQL, with production experience in Azure (ADLS Gen2, ADF) or AWS (S3, Glue).
• Modern Data Stack: Expertise in implementing Unity Catalog and familiarity with dbt or Delta Live Tables (DLT) for modern data orchestration.
• Advanced Features: Experience or interest in building data applications using Databricks Apps and utilizing the latest engine features (Photon, Liquid Clustering).
• Governance & Modeling: Strong understanding of data management principles, including data modeling, metadata management, and data quality frameworks.
• Communication: Fluent English (C1+) for direct client collaboration and the ability to act as a technical advisor to stakeholders.
• Credentials: A commitment to technical excellence, ideally backed by Databricks Certifications (e.g., Data Engineer Professional).

The Offer

Cooperation Models:

• Poland: Available via Employment Contract (UoP) or B2B.
• Romania/Greece: Available via B2B only.
• 100% Remote: Full flexibility to work from anywhere in Poland/ Romania / Greece
• High-End Tech: Apple MacBook Air M4 15" provided to all engineers.
• Referral Bonus: Bonus for bringing other top-tier engineers to the team.
• Professional Growth:
  • Certification Support: Coverage for all Databricks technical certifications.
  • Industry Leadership: Support in reaching the highest tiers of Databricks expertise (such as the Champion program) tailored to your specific career track.
  • Personal Branding: Opportunities to present at global industry conferences and contribute to technical thought leadership.
  • Expert Mentorship: Direct collaboration with Databricks MVPs and core product teams, giving you a front-row seat to the platform's evolution.

Recruitment Process

• Introductory Call (20 min): Short conversation with our Recruiter to discuss your background and expectations.
• Technical Interview (60 min): Deep dive into your technical skills with our engineering team.
• Optional Client Interview: Required only in specific cases.
• Decision & Offer: We aim to close the process and provide feedback efficiently.