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Databricks Engineer information

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$65.1K

$122.1K

$222.1K

How much do databricks engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for databricks engineer in New York is $122,129.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,100.00 and $145,000.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior Databricks Engineers with extensive experience, specialized skills in big data, cloud platforms, and advanced analytics can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or with significant bonuses and stock options. Such compensation typically requires a combination of technical expertise, leadership roles, and years of industry experience.

Is Databricks Data Engineer in demand?

Databricks Data Engineers are in high demand due to the increasing adoption of cloud-based data platforms and the need for expertise in big data processing, Spark, and cloud environments. Companies seek professionals skilled in data pipeline development, ETL processes, and cloud tools like AWS or Azure, making this a strong job market for qualified candidates.

What are some common challenges faced by Databricks Engineers when working with large-scale data pipelines?

Databricks Engineers often encounter challenges related to optimizing the performance and reliability of large-scale data pipelines. These can include efficiently managing cluster resources, handling data partitioning to prevent bottlenecks, and troubleshooting job failures due to resource constraints or data quality issues. Collaboration with data scientists, analysts, and DevOps teams is essential to ensure seamless integration and deployment of production workflows. Staying current with evolving Databricks features and best practices also plays a key role in overcoming these challenges.

How much does a Databricks engineer make?

A Databricks engineer's salary typically ranges from $100,000 to $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized skills in Spark, cloud platforms, or data engineering may earn higher compensation. Salaries can also vary based on industry demand and certifications held.

Is Databricks a high paying job?

A Databricks Engineer typically earns a high salary due to the specialized skills required in cloud computing, big data processing, and Spark platform expertise. Compensation varies based on experience, location, and certifications, but it is generally above average for data engineering roles.

What is a Databricks Engineer?

A Databricks Engineer is a data engineering professional who specializes in using the Databricks platform to build, manage, and optimize data pipelines and analytics solutions. They work with big data technologies like Apache Spark, Delta Lake, and cloud services to process and analyze large datasets efficiently. Their role often involves developing ETL (extract, transform, load) workflows, setting up data lakes, and ensuring data quality and performance for business intelligence and machine learning applications.

What are the key skills and qualifications needed to thrive as a Databricks Engineer, and why are they important?

To thrive as a Databricks Engineer, you need strong expertise in big data processing, cloud platforms (like AWS or Azure), and proficiency with languages such as Python, SQL, and Scala, often supported by a degree in computer science or a related field. Familiarity with Apache Spark, Databricks Workspace, version control systems like Git, and relevant Databricks certifications are typically required. Strong analytical thinking, collaboration, and effective communication skills help you understand business needs and work seamlessly with data teams. These skills ensure efficient data pipeline development, scalable analytics solutions, and successful integration of Databricks into organizational workflows.
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Databricks Engineer jobs near you
Staff Software Engineer - Agent Quality

Staff Software Engineer - Agent Quality

Databricks

New York, NY

Other

Re-posted 14 days ago

Job description

Staff Software Engineer - Agent QualityP-1215

At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization is pushing the frontier of next-generation enterprise AI. We believe a company's data is its greatest competitive advantage, and we're building the models and agents that unlock it. Our work spans the full stack, from model training to advanced multi-agent systems. 

As a Staff Software Engineer - Agent Quality, you will be a founding member of a new team focused on evaluating and continuously improving Databricks' AI Agents. You will design and scale the infrastructure, tooling, and developer workflows that let researchers and engineers evaluate agents rigorously - driving a flywheel where evaluation results feed directly back into agent improvement across the full lifecycle, from development and training to production.

The impact you will have
  • Stand up the foundational evaluation infrastructure for Genie Agents, enabling rigorous benchmarking, regression detection, and quality measurement across research and product teams.
  • Build the flywheel that connects evaluation results back into agent improvement - closing the loop between production signals, training, and iterative development.
  • Shape the long-term technical direction for agent quality infrastructure, with real influence over how Databricks measures and improves its first-party agents and agent development platform.
  • Help shape the long-term technical direction for agent quality infrastructure as Databricks expands its first-party agents and agent development platform.
What we look for
  • 6+ years industry experience building software systems
  • Strong Python programming skills, with experience building production or research infrastructure
  • Experience building or operating distributed systems, data pipelines, or large-scale infrastructure with a focus on reliability, correctness, and operational maturity
  • Ability to design pragmatic but rigorous systems that produce trustworthy, reproducible signals for complex applications
  • Comfort working across ambiguous research and product boundaries, and partnering with both researchers and engineers to turn ideas into robust internal platforms
  • A high bar for technical quality, strong ownership, and the ability to influence roadmap and execution across multiple teams
Nice to have
  • Experience with devtools, CI/CD platforms, testing frameworks, observability tooling, or benchmarking infrastructure
  • Familiarity with how LLM or agent quality is measured - whether through evals, experimentation platforms, or production monitoring

Apply