Lead Data Engineer - Python/PySpark/Databricks/AWS/AI at JPMorgan Chase
Atlanta, GA
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Jul 23, 2026
Atlanta, GA
Jul 24, 2026
What this job asks for AI summary
A senior data engineering role focused on building and maintaining data pipelines, platforms, and models within a large financial services consumer banking division. Day-to-day work spans data collection, storage, access, and analytics architecture, including database backup and recovery strategies, access control evaluation, and data modeling using statistical and mathematical methods. Suits engineers with deep Python, PySpark, Databricks, Snowflake, and AWS experience who are comfortable incorporating AI-assisted tooling into engineering workflows.
Senior level · 5+ years · Full-time
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $142,568 (middle half $111,775–$173,013).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (6)
The job title uses 'Lead' rather than a standard seniority band (Junior/Senior/Staff/Principal). The requirements — 5+ years of applied experience, end-to-end data lifecycle ownership, and independent evaluation of access controls — support a Senior classification.
SOC classification is a genuine judgment call: the role spans data pipeline/architecture work (15-1243 Database Architects) and data modeling with linear algebra, statistics, and geometrical algorithms (15-2051 Data Scientists). The pipeline and platform delivery emphasis was treated as primary.
No work location is specified in the posting; the CBSA field is left blank. The role is at JPMorganChase Consumer & Community Banking but no city or state is stated.
Compensation is described qualitatively (competitive total rewards, base salary determined by role/experience/location) with no numeric figures provided.
AI capabilities are listed as both required and preferred in the posting, but they are framed as practices/habits (validation, auditability) rather than a specific named tool, so no AI skill entry was emitted.
Kafka is listed under Preferred as 'Kafka or any streaming technology'; Splunk and Dynatrace appear together under Preferred hands-on experience.
Read the full posting
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