Vice President, Lead Analytics Engineer

JPMorgan Chase

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Quick summary

Work type: On-site
Location: Newark, DE
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $190k

$132k most similar roles pay here $236k

This listing doesn't post a salary. Most similar roles pay $155,000–$225,675.

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 1174 open roles on FindRole.

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At a glance

TL;DR · Vice President, Lead Analytics Engineer

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As a Vice President, Lead Analytics Engineer within the Data Analytics & Intelligent Automation team, you will execute the analytics engineering roadmap to enable cloud-native business intelligence and analytics. You will design end-to-end Lakehouse stacks using Databricks, Delta Lake, Unity Catalog, Delta Live Tables, and Databricks SQL while building ingestion pipelines in Python and PySpark. Your role involves creating governed semantic models for self-service consumption and translating complex risk data into executive narratives. You will utilize tools such as Alteryx, Prophecy, Snowflake, Tableau, and Sigma to deliver actionable insights. The position requires expertise in ETL design, advanced SQL, and schema modeling within a regulated environment. You will manage data governance, lineage, and access controls while advising on cloud analytics strategies to support risk management and compliance functions through scalable adoption patterns and technical enablement.

Skills

Databricks Delta Lake Unity Catalog Delta Live Tables Python PySpark SQL Tableau Sigma Alteryx Prophecy Snowflake AWS Git Redshift Oracle PostgreSQL ETL Data Mesh

What you'll do

Architect and implement end-to-end data pipelines using Databricks, Delta Lake, and Unity Catalog for governance and lineage.
Build ingestion and integration pipelines using Python and PySpark to move data into the Lakehouse.
Design a governed self-service layer in Databricks SQL featuring curated semantic models and intuitive views.
Partner with data owners to manage cataloging, lineage, ownership, and access entitlements.
Advise on cloud analytics strategies and define enablement patterns for new users and citizen developers.
Translate complex risk data into clear, actionable narratives and executive-ready dashboards in Tableau or Sigma.
Utilize AI tools like GitHub Copilot to accelerate development while ensuring the accuracy of all generated code.

What we're looking for

Degree or certification in Computer Science, Information Systems, Data Engineering, or a related field.
7–8+ years of experience in data/analytics engineering or BI within a regulated environment.
Proficiency in ETL pipeline design, advanced SQL, and production-grade Python and PySpark.
Expertise in Databricks Lakehouse architecture, including Delta Lake, Unity Catalog, and Delta Live Tables.
Experience with enterprise BI tools such as Tableau and Sigma to deliver executive-ready dashboards.
Strong schema modeling experience for integrated datasets and knowledge of data mesh concepts.
Ability to communicate complex technical narratives to senior, non-technical stakeholders.
Experience with Snowflake, Redshift, Oracle, SQL Server, PostgreSQL, Alteryx, Prophecy, or AWS (preferred).

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