Lead Data Engineer (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VA · New York, NY
Salary: $197,300–$225,100 / yr
Posted: 16 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $188k

This role $211k

$147k most similar roles pay here $233k

This role pays more than 68% of similar roles. Most pay $155,375–$220,069 — the shaded band above. At the midpoint, this role pays about $211k versus about $188k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Lead Data Engineer (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)

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Join our dynamic Enterprise Platforms Technology team as a Lead Data Engineer and lead the design and implementation of scalable data solutions using Python, AWS, and SQL. You will work closely with cross-functional teams to build robust data pipelines, optimize data storage and retrieval processes, and integrate advanced analytics tools like GenAI into existing systems. Ideal candidates have 4+ years of experience with distributed computing tools such as MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL, alongside a Master’s Degree to complement their technical expertise. This role involves tackling complex business challenges at scale and driving innovation in data engineering practices within a fast-paced enterprise environment.

Skills

Python AWS SQL MapReduce Hadoop Hive EMR Kafka Spark Gurobi MySQL

What you'll do

Design and implement large-scale data processing systems using Python and AWS.
Optimize data pipelines for efficiency and scalability on distributed computing platforms.
Develop and maintain SQL databases to support enterprise-level analytics needs.
Integrate generative AI models into existing data infrastructure for enhanced capabilities.
Troubleshoot and resolve complex issues in data engineering environments.

What we're looking for

Bachelor’s Degree required.
4+ years of experience with distributed computing tools like MapReduce, Hadoop, and Spark.
Proficiency in Python, AWS services, and SQL.
Experience with data engineering and GenAI technologies preferred.
Master’s Degree preferred for advanced roles.

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