JobHabor

Lead Software Engineer

JPMorganChase

Location
Wilmington
Workplace
Onsite
Employment
Full Time
Salary
Apply on the employer’s site

Posted 1mo ago

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers and businesses. As a Lead Software Engineer - Python/PySpark/Databricks/AWS, you will be a core technical contributor responsible for enhancing and delivering market-leading technology products while supporting the firm’s business objectives.

Responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Develops secure high-quality production code, and reviews and debugs code written by others
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
  • 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
  • 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

Skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience
  • 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
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Experience building and operating Databricks Lakehouse solutions hosted on Amazon Web Services (AWS), including Amazon S3, Identity and Access Management (IAM), Key Management Service (KMS), basic networking concepts (VPC/security groups), and logging/auditing; Experience using Delta Lake (ACID-compliant tables, partitioning strategies, schema evolution) and Apache Spark on Databricks, including performance optimization (cluster sizing, skew mitigation, join strategies, caching, and file sizing/compaction); Experience delivering batch and streaming data pipelines (Structured Streaming, incremental processing, backfills, late-arriving data handling) and implementing governance/security controls in Databricks (e.g., Unity Catalog, table/column-level permissions, credential passthrough where applicable), with operational ownership including monitoring/alerting, incident response, root-cause analysis (RCA), and service level objective/service level agreement (SLO/SLA) management
  • Advanced in one or more programming language(s) including Python, PySpark
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Architect Databricks Lakehouse solutions, including bronze/silver/gold (or equivalent) layering and domain-oriented data products; implement resilient, scalable ingestion from AWS sources into Databricks using batch and streaming patterns (including CDC where required)
  • Build maintainable pipelines using Delta Live Tables (DLT) and/or Databricks Jobs/Workflows with modular design, documentation, and runbooks; ensure production readiness through retries, checkpointing, idempotency, safe re-runs, and defined replay/backfill procedures; implement testing practices including unit/integration tests, data quality checks, and contract testing; Apply governance-by-design controls (least privilege, PII classification, auditing, lineage/metadata, controlled sharing/consumption); optimize Spark/Delta performance and cost (cluster right-sizing, storage layout, job/warehouse spend); lead design/code reviews and mentor engineers; partner cross-functionally with stakeholders and security/platform teams; deliver CI/CD and infrastructure-as-code for Databricks + AWS with promotion across environments and strong version control/code review discipline
  • 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
  • AI experience

Benefits

  • Comprehensive health care coverage
  • On-site health and wellness centers
  • A retirement savings plan
  • Backup childcare
  • Tuition reimbursement
  • Mental health support
  • Financial coaching

Company Overview

  • With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. It was founded in 2000, and is headquartered in New York, New York, USA, with a workforce of 10001+ employees. Its website is https://www.jpmorganchase.com.

Company H1B Sponsorship

  • JPMorganChase has a track record of offering H1B sponsorships, with 1787 in 2026, 3470 in 2025, 3469 in 2024, 3395 in 2023, 3594 in 2022, 2515 in 2021, 2495 in 2020. Please note that this does not guarantee sponsorship for this specific role.

Skills

  • Python
  • PySpark
  • Databricks
  • Lakehouse
  • Amazon Web Services (AWS)
  • Amazon S3
  • AWS Identity and Access Management (IAM)
  • AWS Key Management Service (KMS)
  • AWS VPC
  • Delta Lake
  • Apache Spark
  • Structured Streaming
  • Delta Live Tables (DLT)
  • Databricks Jobs/Workflows
  • CI/CD
  • Infrastructure as Code
  • Unit Testing
  • Integration Testing
  • Contract Testing
  • Secure Coding
  • AI-assisted Software Development Tools
  • Performance Optimization
  • Incident Response
  • Root Cause Analysis (RCA)
  • Service Level Objective/Agreement (SLO/SLA) Management
  • Data Governance Controls
  • PII Classification
  • Data Governance Controls Auditing
  • Data Governance Controls Lineage
  • Data Governance Controls Metadata
  • Unity Catalog
  • Credential Passthrough

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