Lead Data Engineer

JPMorgan Chase

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Houston, TX
Employment
Full-time
Posted
20 days ago
Freshness
Confirmed live today

Market check

Salary context

How this pay compares to similar roles

Similar $169k
$117k $221k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$211,200.

Based on 240 similar postings.

Employer

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 1226 open roles on FindRole.

Listed pay typically runs $156,750–$215,000 across 5 roles with salary data.

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At a glance

TL;DR · Lead Data Engineer

The Corporate Sector - Lead Data Engineer joins a team building secure, scalable data pipelines and platforms for collection, access, and analytics. This role leads architecture and engineering for scalable backup, recovery, immutable-data protection, and recovery-assurance services across various storage tiers. You will build cloud-native capabilities using AWS services, infrastructure as code, and CI/CD pipelines while designing role-based observability dashboards using Grafana, Dynatrace, and Tableau. Responsibilities include data modeling using linear algebra and statistical algorithms, managing relational and NoSQL estates, and implementing SRE principles to meet RPO/RTO targets. You will perform hands-on pipeline engineering with Spark, SQL, and Python or Java. The work focuses on enterprise data protection, cyber resilience, and providing audit-ready evidence for platform controls within regulated financial services environments.

What you'll do

  • Design and maintain role-based observability dashboards using Grafana, Dynatrace, and Tableau to monitor platform health and risk.
  • Define and govern SLIs, SLOs, and operational health KPIs for data platforms and backup services.
  • Own the strategy for database backup, recovery, archiving, and retention across relational and NoSQL estates.
  • Build cloud-native capabilities using AWS services, infrastructure as code, and CI/CD pipelines.
  • Implement SRE principles by maintaining runbooks, leading incident responses, and tracking reliability metrics.
  • Design preventive controls and automated validation to ensure data asset security and audit-ready recovery evidence.
  • Perform hands-on data architecture, including dimensional modeling, advanced SQL tuning, and distributed processing with Spark.
  • Set engineering standards, perform code reviews, and mentor engineers while managing technical debt and cross-team delivery.

What we're looking for

  • 8+ years of applied engineering experience leading production-critical systems.
  • Experience with both relational and NoSQL databases.
  • Proficiency in Python and at least one other language such as Java, Go, or C#.
  • Advanced AWS experience including IAM/security, networking, and infrastructure automation.
  • Hands-on experience with Dynatrace and Grafana for observability and monitoring.
  • Experience with CI/CD platforms like Jenkins, GitLab, or GitHub Actions.
  • Knowledge of linear algebra, statistical, and geometric algorithms.
  • Experience with Kubernetes/OpenShift and containerized platform operations (preferred).

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