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Software Engineer III - Python, Databricks and AWS

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 5 days ago

No clicks

**Software Engineer III - Python, Databricks and AWS** Leverage Python, Databricks, and AWS to build resilient data pipelines. Maintain architectures, enforce governance, optimize performance, and manage costs. Collaborate in agile teams to deliver secure, scalable data solutions. Requires 3+ years of software engineering experience, data engineering skills, and hands-on Databricks and AWS proficiency.

Compensation
Not specified USD

Currency: $ (USD)

City
Jersey City
Country
United States

Full Job Description

Location: Jersey City, NJ, United States

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 firms 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; 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
Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team

Software Engineer III - Python, Databricks and AWS

Compensation

Not specified USD

City: Jersey City

Country: United States

J.P. Morgan logo
Bulge Bracket Investment Banks

5 days ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

**Software Engineer III - Python, Databricks and AWS** Leverage Python, Databricks, and AWS to build resilient data pipelines. Maintain architectures, enforce governance, optimize performance, and manage costs. Collaborate in agile teams to deliver secure, scalable data solutions. Requires 3+ years of software engineering experience, data engineering skills, and hands-on Databricks and AWS proficiency.

Full Job Description

Location: Jersey City, NJ, United States

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 firms 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; 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
Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team