Software Engineer II - Databricks

As a Software Engineer II at JPMorgan Chase within our Corporate Investment Bank, Payments Technology team, you’ll design, build, and operate scalable data pipelines and analytics workloads on the Databricks Lakehouse platform. You’ll partner with data analysts, data scientists, and application teams to deliver trusted datasets, performant ETL/ELT pipelines, and well-governed data products.

Job responsibilities

• Design and implement batch and streaming data pipelines using Databricks (Spark), Delta Lake, and orchestrators (e.g., Workflows, Airflow, ADF).
• Develop and optimize Spark jobs (PySpark/Scala) and SQL transformations for performance, reliability, and cost efficiency.
• Build and maintain curated data models (bronze/silver/gold), data quality checks, and automated testing.
• Implement CI/CD for notebooks and code (Git-based workflows), and automate deployments across environments.
• Manage and tune Databricks clusters, jobs, and configurations; monitor production workloads and resolve incidents.
• Integrate multiple data sources (cloud storage, relational DBs, APIs, event streams) and implement robust ingestion patterns.
• Apply data governance and security best practices (access controls, secrets management, lineage/metadata, auditing).
• Create clear documentation for pipelines, data contracts, and operational runbooks.
• Leverage enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity.
• Apply knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation.

Required qualifications, skills and capabilities

• Experience with building data pipelines on Databricks and/or Apache Spark in production.
• Strong coding skills in Python (PySpark) and SQL (Scala a plus).
• Hands-on experience with Delta Lake (MERGE/UPSERT patterns, schema evolution, partitioning, Z-ORDER, OPTIMIZE/VACUUM).
• Experience with orchestration and scheduling (Databricks Workflows, Airflow, Azure Data Factory, etc.).
• Familiarity with cloud data platforms (AWS/Azure/GCP) and storage (S3/ADLS/GCS).
• Solid understanding of data engineering fundamentals: data modeling, ETL/ELT patterns, reliability, observability, and performance tuning.
• Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment.
• Understanding of responsible AI use in engineering workflows, including data sensitivity considerations.

Preferred qualifications

• Experience with streaming (Structured Streaming, Kafka/Event Hubs/Kinesis).
• Experience implementing data quality frameworks (Great Expectations, DQ) and data testing in CI.
• Exposure to Unity Catalog (or similar) for governance and fine-grained permissions.

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.