Lead Software Engineer - Databricks

Be an integral part of an agile team that’s constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Lead Software Engineer-Databricks at JPMorgan Chase within our Corporate Sector’s Enterprise Technology team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

• Lead the architecture and delivery of high-throughput, low-latency data pipelines on Databricks using Apache Spark (Core, SQL, Structured Streaming), driving performance, reliability, and scalability.
• Establish and evolve Lakehouse patterns with Delta Lake (ACID transactions, schema evolution, time travel, Z-ordering, compaction) to ensure performant, maintainable data platforms at scale.
• Own Databricks cluster strategy and configuration, including runtime selection, autoscaling, driver/executor sizing, Spark configurations, init scripts, cluster policies, pools, and instance profiles.
• Orchestrate and automate pipelines and jobs using Databricks Workflows, integrating with AWS eventing and orchestration services as needed.
• Design secure ingestion and transformation frameworks leveraging Databricks services, including Delta or unmanaged table design, ingestion task creation, and Airflow DAGs to produce trusted and refined datasets.
• Enforce data quality, lineage, and governance using Unity Catalog and/or AWS Glue Catalog, embedding expectations and validation directly into pipelines.
• Drive Spark and Databricks performance engineering and tuning (partitioning and file sizing, AQE, broadcast joins, shuffle tuning, caching, spill/memory control, job right-sizing, and liquid clustering/partitioning keys) to optimize cost and throughput.
• Build and maintain reusable libraries, frameworks, and APIs in Python and/or Java, ensuring strong unit, integration, and data validation test coverage.
• Implement CI/CD for data projects using Git-based workflows, Terraform-based infrastructure deployments and environment promotion, and automated releases; champion engineering standards, code reviews, and enterprise-authorized AI-assisted engineering practices (e.g., code review/refactoring, test acceleration, and incident/root-cause analysis) with consistent validation (secure coding, peer review, automated testing) and reuse of proven patterns.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Formal training or certification on software engineering concepts and 5+ years applied experience.
• Advanced experience in software engineering and data engineering, including significant production delivery with Apache Spark on Databricks and/or AWS EMR.
• Advanced hands-on Databricks expertise across Delta Lake, Unity Catalog, Workflows, Repos/notebooks, and SQL Warehouses, including cluster configuration and optimization.
• Proven ability to architect, build, and operate reliable ETL/ELT data pipelines (batch and streaming), including schema design/evolution, SLAs, and reliability engineering practices.
• Deep Spark performance tuning skills, with experience diagnosing bottlenecks and optimizing jobs for scalability, cost, and runtime efficiency.
• Strong programming proficiency in Python and/or Java for data processing, platform tooling, and automation.
• Strong SQL and…