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 5+ 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; incremental processing; backfills; late-arriving data).
- Strong AWS fundamentals for data platforms: S3, IAM, KMS, networking basics (VPC/security groups), logging/auditing.
- Experience implementing data governance/security controls in Databricks (e.g., Unity Catalog, table/column permissions, credential passthrough patterns as applicable)
- Demonstrate experience with reliability: monitoring/alerting, incident response, RCA, and SLO/SLA management
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies
- Exposure to cloud technologies
About Us
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
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. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
JPMorganChase New York, New York, USA Office
270 Park Avenue, New York, NY, United States, 10017-2014
JPMorganChase New York, New York, USA Office
4 Metrotech Center, New York, NY, United States, 11201
Similar Jobs
What you need to know about the NYC Tech Scene
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
