Databricks Performance and FinOps Engineer

Job Description

Job Description

Databricks Performance and FinOps Engineer

Job Summary

The Databricks Performance and FinOps Engineer makes the platform faster and cheaper at the same time, and can prove both. This role owns compute strategy, workload tuning, and the cost visibility that lets leadership see where spend is going and why. It is a good fit for engineers who enjoy the forensic side of the work and can hold a defensible position when someone wants to solve a performance problem by buying more compute.

Key Responsibilities

• Analyze workload and cluster telemetry to find the jobs driving disproportionate cost or runtime

• Tune Spark jobs and SQL workloads through partitioning, caching, join strategy, file layout, and skew handling

• Define compute strategy across job clusters, serverless, SQL warehouses, and pools

• Build cost allocation and chargeback reporting using system tables, tags, and budget policies

• Set and enforce cluster policies and autoscaling configuration to prevent avoidable spend

• Establish performance baselines and service level objectives for critical pipelines

• Run cost reviews with engineering and finance stakeholders and translate technical drivers into budget language

• Advise on photon adoption, runtime upgrades, and instance type selection

Required Skills

• 5 years in data engineering or platform engineering with a focus on performance

• Deep Spark tuning experience and fluency reading the Spark UI, query profiles, and execution plans

• Hands on experience with Databricks system tables and usage analytics

• Understanding of cloud pricing models for compute and storage across at least one major cloud

• Strong SQL and Python

• Ability to build reporting that non technical stakeholders will actually use

Preferred Skills

• FinOps Certified Practitioner credential

• Experience with liquid clustering, predictive optimization, and photon workload assessment

• Prior ownership of a platform cost reduction program with documented results

• Experience with tagging strategy and enterprise cloud cost tooling

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