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Databricks

Staff Software Engineer - Database Engine Internals

Belgrade, Serbia

Location
Belgrade, Serbia
Work
Not stated
Employment
Not stated
Level
Lead / staff
Function
Engineering
Pay
Not stated
Posted
17 months ago

About the role

P-1416

Our mission at Databricks is to radically simplify the whole data lifecycle from ingestion to ETL, BI, and all the way up to ML/AI with a unified platform. To achieve this goal, we believe the data warehouse architecture as we know it today will be replaced by a new architectural pattern, Lakehouse (CIDR 2021 paper), open platforms that unify data warehousing and advanced analytics. This new architecture will help address several major challenges, including data staleness, reliability, total cost of ownership, data lock-in, and limited use-case support.

To achieve this vision, Databricks is building the next generation (decoupled) query engine and structured storage system that can outperform specialized data warehouses in relational query performance. Yet we will retain the expressiveness and robustness of general purpose systems such as Apache Spark™ to support diverse workloads ranging from ETL to data science. You will be part of this multi-year journey.

As part of this team, you will design these next-generation systems that leapfrog state-of-the-art within the following areas:

  • Query compilation and optimization
  • Distributed query execution and scheduling
  • Vectorized execution engine
  • Data security
  • Resource management
  • Transaction coordination
  • Efficient storage structures (encodings, indexes)
  • Automatic physical data optimization

The responsibilities you will have

  • Drive requirements clarity and design decisions for ambiguous problems
  • Produce technical design documents and project plans
  • Develop new features
  • Mentor more junior engineers
  • Test and rollout to production, monitoring.

What we look for

  • A passion for database systems, storage systems, distributed systems, language design, or performance optimization
  • Are comfortable working towards a multi-year vision with incremental deliverables
  • Be customer-oriented and focused on having an impact
  • 7+ years of experience working in a related system
  • Optional: PhD in databases or distributed systems

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Source

Posted by Databricks on their own hiring page, databricks.com. OptiTalent shows it as published, read 06 Nov 2026 23:58 UTC; the original is the reference.

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