Software Engineer III - Python, Databricks and AWS

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer at JPMorgan Chase within Corporate Technology - Global Finance Technology, you serve as a seasoned member of an agile team that works to enhance, build, and deliver data collection, storage, access, and analytics solutions in a secure, stable, and scalable way.

As a core technical contributor, you are responsible for maintaining critical data pipelines and architectures across multiple technical areas within various business functions in support of the firm's business objectives.

Job responsibilities


* Deliver ingestion at scale: implement resilient ingestion from AWS sources into Databricks (batch + streaming), including CDC where needed.


* Build maintainable pipelines: use Delta Live Tables (DLT) and/or standard Jobs with clear modular structure, testing, and documentation.


* Operational excellence: productionize workloads via Databricks Workflows/Jobs, robust retries, checkpointing, idempotency, and safe re-runs.


* Governance by design: enforce least privilege, data classification (PII), auditing, lineage/metadata, and controlled sharing/consumption.


* Performance & cost management: tune Spark/Delta workloads, right-size clusters, optimize storage layout, and manage job/warehouse spend.


* CI/CD and IaC: Terraform (preferred) for Databricks + AWS resources; promotion across environments.
Testing: unit/integration tests for transformations, data quality checks, contract testing, and replay/backfill procedures.


* Version control & code review discipline; clear documentation and runbooks


* Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.


* 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.

Required qualifications, capabilities, and skills


* Formal training or certification on software engineering concepts and 3+ years hands on Software Development Life Cycle experience


* Experience in data engineering experience building and maintaining data pipelines.


* Hands-on experience building and operating a Databricks Lakehouse Hosted in AWS


* Experience with Delta Lake (ACID tables, partitioning, schema evolution,


* Proven experience with Spark on Databricks (performance tuning, cluster sizing, skew mitigation, joins, caching, file sizing).


* Experience with streaming and batch pipelines (Structured Streaming; incre...