Software Engineer III - Python, Databricks and AWS

JPMorgan Chase & Co. • Plano, TX

4d

About The Position

As a Software Engineer at JPMorgan Chase within Corporate Technology - Global Finance Technology, you serve as a seasoned member of an agile team that enhances, builds, and delivers secure, stable, and scalable data collection, storage, access, and analytics solutions. As a core technical contributor, you maintain critical data pipelines and architectures across technical areas and business functions in support of firm objectives.

The role focuses on large-scale batch and streaming ingestion from AWS into Databricks; maintainable, tested, and documented pipelines using Delta Live Tables and/or Databricks Jobs; production operations and reliability; governance and security; workload performance and cost management; and CI/CD and infrastructure as code. You will also use enterprise-authorized AI coding and automation tools to support software development, validating outputs through peer review, automated testing, and secure coding practices.

Requirements

• Formal training or certification in software engineering concepts.
• At least 5 years of hands-on Software Development Life Cycle experience.
• Data engineering experience building and maintaining data pipelines.
• Hands-on experience building and operating a Databricks Lakehouse hosted on AWS.
• Experience with Delta Lake, including ACID tables, partitioning, and schema evolution.
• Proven experience with Spark on Databricks, including performance tuning, cluster sizing, skew mitigation, joins, caching, and file sizing.
• Experience with streaming and batch pipelines, including Structured Streaming, incremental processing, backfills, and late-arriving data.
• Strong AWS fundamentals for data platforms, including S3, IAM, KMS, networking basics such as VPC and security groups, and logging and auditing.
• Experience implementing Databricks data governance and security controls, such as Unity Catalog, table and column permissions, and credential passthrough patterns as applicable.
• Experience with reliability practices, including monitoring and alerting, incident response, root cause analysis, and SLO/SLA management.
• Understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective use.
• Hands-on experience using enterprise-authorized AI-assisted software development tools for tasks such as coding, test creation, troubleshooting, or documentation, and ability to critically evaluate, validate, and refine generated outputs for correctness, performance, and security.

Nice To Haves

• Familiarity with modern front-end technologies.
• Exposure to cloud technologies.

Responsibilities

• Implement resilient, large-scale batch and streaming ingestion from AWS sources into Databricks, including change data capture where needed.
• Build maintainable pipelines using Delta Live Tables and/or standard Databricks Jobs with modular structure, testing, and documentation.
• Productionize workloads through Databricks Workflows and Jobs, including robust retries, checkpointing, idempotency, and safe re-runs.
• Enforce governance controls, including least privilege, PII classification, auditing, lineage and metadata management, and controlled data sharing and consumption.
• Tune Spark and Delta workloads, right-size clusters, optimize storage layout, and manage job and warehouse costs.
• Use Terraform, preferred, for Databricks and AWS resources and promote changes across environments.
• Develop unit and integration tests, data quality checks, and contract tests, and support replay and backfill procedures.
• Apply version control and code review practices and provide clear documentation and runbooks.
• Use enterprise-authorized AI coding-assistance tools to improve code quality, delivery speed, and productivity, while validating their outputs through peer review, automated testing, and secure coding standards.
• Apply SDLC toolchain tools, including authorized AI-assisted development and automation capabilities, and contribute reusable learnings and patterns to improve team effectiveness.

Benefits

• Competitive total rewards package.
• Comprehensive health care coverage.
• On-site health and wellness centers.
• Retirement savings plan.
• Backup childcare.
• Tuition reimbursement.
• Mental health support.
• Financial coaching.
• Eligible roles may receive commission-based pay and/or discretionary incentive compensation in the form of cash and/or forfeitable equity.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed