Lead Software Engineer, Data Engineering

JPMorgan Chase

Confirmed live yesterday Low trust

Quick summary

Work type
On-site
Location
Plano, TX
Posted
42 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $203k
$187k most similar roles pay here $230k

This listing doesn't post a salary. Most similar roles pay $192,050–$214,000.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Lead Software Engineer, Data Engineering

Lead Software Engineer - Data Engg. - Databricks / Snowflake joins the Identity and Access Management Data team to design, develop, and maintain scalable data processing solutions. This role involves building a control plane for enterprise data pipelines to standardize definition, scheduling, and governance while developing self-service APIs, SDKs, and configuration-driven onboarding. The engineer will build and maintain data pipelines and processing workflows using Python, PySpark, SQL, Databricks, and AWS services like S3, ECS, SNS/SQQ, and Lambda. Key responsibilities include ensuring data quality, security, and lineage through observability tools while leading the full SDLC and mentoring engineers on modern practices. The role focuses on solving complex technical problems in the domain of identity and access management by creating robust infrastructure for large-scale processing, automated remediation patterns, and integrating enterprise-authorized AI-assisted engineering tools to improve code quality and delivery speed.

What you'll do

  • Design and build a control plane for enterprise data pipelines to standardize definition, scheduling, and governance.
  • Develop self-service APIs, SDKs, and configuration-driven onboarding tools with consistent guardrails and metadata tracking.
  • Build and maintain scalable data pipelines and processing workflows using Python, PySpark, SQL, and Databricks on AWS.
  • Ensure data quality, security, and lineage through standardized observability, dashboards, and automated remediation patterns.
  • Lead the full software development life cycle including requirements, design, testing, and production support for platform services.
  • Mentor engineers and lead communities of practice to drive adoption of modern engineering practices and tools.
  • Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.

What we're looking for

  • Formal training or certification on software engineering concepts and 5+ years of applied experience.
  • Proven experience in data management and ETL/ELT for large-scale processing using SQL, Python, and PySpark with performance tuning.
  • Hands-on experience with Databricks/Spark and cloud data lake patterns integrated with AWS services like S3, ECS, SNS/SQS, and Lambda.
  • Proven experience building platform services or control planes including API design, configuration-driven systems, and versioning.
  • Strong understanding of data quality, security-by-design, lineage, and IAM/least privilege principles.
  • Strong production engineering mindset including observability, monitoring, alerting, and incident response for always-on services.
  • Proficiency in CI/CD and release engineering using standard tooling for automated testing and safe deployments.
  • Demonstrated experience leading the use of approved AI-assisted software development tools while ensuring security and quality standards.

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