Lead Software Engineer - Python, Databricks and AWS

Fairygodboss; Jersey City (NJ); On-site; USD 152,000 - 215,000; Full time

Job summary

JPMorgan Chase in Jersey City, NJ, is seeking a Lead Software Engineer to architect and deliver scalable data platforms on Databricks Lakehouse hosted in AWS. You will drive ingestion pipelines, implement robust testing, and mentor engineers to uphold best practices in secure, cost-aware data engineering.

You will influence design reviews, establish reliability practices, and promote responsible AI use across the team while partnering with security and platform teams to align with enterprise

Qualifications

• Formal training or certification on software engineering concepts and 5+ years hands on Software Development Life Cycle experience
• Strong data engineering experience, including proven leading delivery/architecture for multi-team data platforms.
• Hands-on experience building and operating a Databricks Lakehouse Hosted in AWS
• Deep 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).
• Demonstrated experience leading effective use of approved AI-assisted software development tools with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
• Demonstrated ownership of reliability: monitoring/alerting, incident response, RCA, and SLO/SLA management.

Responsibilities

• Architect the lake house: design bronze/silver/gold layers and data products
• Deliver ingestion at scale from AWS into Databricks (batch + streaming; include CDC)
• Build maintainable pipelines with Delta Live Tables or Jobs; ensure testing and docs
• Operational excellence: productionize workloads with workflows, retries, checkpointing, idempotency
• Governance by design: enforce least privilege, PII classification, auditing, lineage
• Promote enterprise AI-assisted engineering practices to improve code quality and delivery speed
• Apply SDLC toolchain expertise, including AI-assisted development and automation
• Performance & cost management: tune Spark/Delta workloads, optimize storage, cluster sizing
• Lead and mentor: set standards, review designs, upskill engineers, ensure security alignment
• CI/CD and IaC: Terraform for Databricks + AWS; promote across environments
• Testing: unit/integration tests, data quality checks, replay/backfill procedures

Skills

Databricks Lakehouse

Spark / Delta Lake optimization

AWS fundamentals

Terraform / IaC

Leadership / mentoring

CI/CD automation

Data governance / security

AI-assisted development practices

Education

Formal software engineering training or certification

Experience with SDLC

Tools

Databricks

Delta Lake

Terraform

AWS (S3/IAM/KMS)

Unity Catalog / data governance

Job description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, 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.

Job responsibilities

• Architect the lake house: design bronze/silver/gold (or equivalent) layers, domain data products

• 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.

• 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.

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

• Lead and mentor: set engineering standards, run design reviews, drive code quality, and upskill engineers in Spark/Databricks best practices, cross-functional delivery: translate stakeholder needs into technical plans, communicate tradeoffs, and align with security/platform teams.

• 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.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years hands on Software Development Life Cycle experience

• Strong data engineering experience, including proven leading delivery/architecture for multi-team data platforms.

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

• Deep 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).

• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.

• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices

• Demonstrated ownership of reliability: monitoring/alerting, incident response, RCA, and SLO/SLA management.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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

Base Pay/Salary

Jersey City,NJ $152,000.00 - $215,000.00 / year