Corporate Sector - Lead Data Engineer

JPMorgan Chase & Co.; Houston (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a Lead Data Engineer to architect and build secure, scalable data pipelines and platforms for collection, storage, access, and analytics.

You will own observability, data modeling, governance, and platform engineering with an automation-first mindset. Responsibilities include leading backup/recovery strategies, defining SLIs/SLOs, and delivering telemetry across data platforms.

Qualifications

• 8+ years of engineering experience with production-critical systems.
• Experience with relational and NoSQL databases.
• Strong observability, monitoring, incident response, and runbooks.
• Experience with AWS and data protection/backup strategies.

Responsibilities

• Lead architecture and engineering for backup, recovery, and data protection.
• Build role-based observability dashboards using Grafana, Dynatrace, and Tableau.
• Drive automation-first, API-led, self-service platform capabilities.
• Coordinate cross-team delivery with clear SLIs/SLOs and gates.
• Ensure security, controls, and recovery assurance.

Skills

Observability & operations

Security/governance

System design & tradeoffs

Technical leadership

Distributed systems

APIs

Automation frameworks

Python

Tools

Grafana

Dynatrace

Tableau

AWS

Jenkins

GitHub Actions

Job description

Join a team that builds secure, scalable data pipelines and platforms for collection, access and analytics.

As a Lead data Engineer, within the Corporate Sector you will lead architecture and engineering for scalable backup, recovery, immutable-data protection, and recovery-assurance services across data platforms and storage tiers and deliver data collection, storage, access, and analytics platform solutions in a secure, stable, scalable way, with clear SLOs/SLAs and operational readiness gates.

Job Responsibilities

Observability (Dashboards: Grafana, Dynatrace, Tableau):

• Design, build, and maintain role-based observability dashboards for data platforms and backup/recovery services using Grafana, Dynatrace, and Tableau, providing real-time and historical visibility into platform health, performance, and risk posture.
• Define and govern dashboard standards and operating model (golden dashboards, drill-down paths, naming/tagging conventions, ownership, and lifecycle management) to drive consistent adoption across Engineering, SRE, Operations, and Risk.
• Ensure end-to-end instrumentation and telemetry quality so dashboards surface actionable signals (availability, latency, throughput, error rates, saturation) and platform KPIs (job success/failure, lag/backlog, data freshness, restore success, retention coverage).
• Establish and publish SLIs/SLOs and operational health KPIs; translate these into Grafana/Dynatrace visualizations and Tableau reporting for executive and governance stakeholders.

Data Architecture, Modeling, and Governance:

• Generate and govern data models using firmwide tooling; apply linear algebra, statistical, and geometric algorithms where relevant for modeling and optimization.
• Own and continuously improve the strategy for database backup, recovery, archiving, retention, and restore testing across relational and NoSQL estates.

Platform Engineering & Automation:

• Drive an automation-first, API-led, self-service approach that reduces operational toil and improves resilience and customer experience.
• Build cloud-native capabilities using AWS services, infrastructure as code, CI/CD, and modern software engineering practices.

Reliability Engineering (SRE) & Operational Excellence:

• Embed SRE principles by defining and tracking reliability metrics (SLIs/SLOs), implementing observability standards, leading incident learning, and maintaining runbooks and recovery playbooks.
• Participate in an on-call and incident leadership rotation, acting as an escalation point for complex platform and data reliability issues.

Security, Controls, and Recovery Assurance:

• Assess and report on access control effectiveness and data asset security posture; partner with security/risk to remediate gaps.
• Design preventive/detective controls, policy guardrails, automated validation, and audit-ready evidence for platform controls and recovery readiness.
• Deliver telemetry, reporting, and operational intelligence for backup health, compliance, and recovery assurance (coverage, success rates, RPO/RTO attainment).

Technical Leadership & Delivery Management:

• Set engineering standards, perform high-quality code reviews, mentor engineers, and influence stakeholders across product, architecture, security, and SRE.
• Coordinate cross-team delivery with explicit dependencies, milestones, and measurable outcomes; manage technical debt and balance reliability/security work alongside feature delivery.

Core Engineering Scope (Hands-on):

• Data architecture & modeling (lakehouse/warehouse patterns, dimensional modeling, data contracts)
• Advanced SQL (performance tuning, warehousing design)
• Pipeline engineering & orchestration (reliable batch workflows, backfills, SLAs)
• Distributed processing (e.g., Spark; partitioning, joins/shuffles, file formats)

• Data quality & testing (automated checks: schema/freshness/volume/business rules)

Required Qualifications, Capabilities, and Skills

• Typically8+ yearsof applied engineering experience (software engineering or related discipline), including leadingproduction-critical systems; experience with bothrelational and NoSQLdatabases; Strong capability in: observability & operations (monitoring, lineage, incident response/runbooks), security/privacy/governance (least privilege, encryption concepts, auditability), system design & tradeoff analysis (scalability, latency, reliability, cost), and technical leadership (standards, mentoring, stakeholder alignment).
• Proficient across the data lifecycle (ingestion, modeling, storage, serving, governance, operations) with demonstrated experience buildingdistributed systems,platform services,APIs, andautomation frameworks.
• Strong knowledge ofenterprise data protection, backup/recovery, cyber resilience, immutable storage, retention, and recovery testing.
• AdvancedAWSexperience spanning backup/data protection services,IAM/security, networking fundamentals, observability, and infrastructure automation.
• Hands-on experience with observability/monitoring platforms such asDynatraceandGrafana and proficiency inPythonand at least one additional language (e.g.,Java, Go, C#).
• Experience with CI/CD platforms (e.g.,Jenkins, GitLab, GitHub Actions) and implementing database backup/recovery/archiving strategies with measurableRPO/RTOtargets.
• Proficient knowledge oflinear algebra, statistical, and geometric algorithms; ability to translate security, control, and regulatory requirements into engineered solutions and operational processes.

Preferred Qualifications, Capabilities, and Skills

• Experience withKubernetes/OpenShiftand containerized platform operations.
• Experience with database platforms andcyber-recovery / isolated recoverysolutions.
• Experience building operational analytics (health/compliance dashboards, evidence automation) forregulated financial servicesenvironments.