Sr. Lead Data Engineer (Enterprise Platforms Technology)

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VA · New York, NY · Richmond, VA
Salary: $229,900–$262,400 / yr
Posted: 60 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $197k

This role $246k

$156k most similar roles pay here $274k

This role pays more than 89% of similar roles. Most pay $167,500–$226,600 — the shaded band above. At the midpoint, this role pays about $246k versus about $197k for comparable roles.

Based on 239 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 · Sr. Lead Data Engineer (Enterprise Platforms Technology)

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As a Senior Lead Data Engineer at Enterprise Platforms Technology in New York, you will lead the design and implementation of large-scale data solutions, focusing on distributed computing tools such as MapReduce, Hadoop, Hive, EMR, Kafka, Spark, and MySQL. Your day-to-day responsibilities include developing robust data models and warehousing strategies to support enterprise-level analytics and decision-making processes. You will also leverage AI-assisted coding tools like Claude Code and GitHub Copilot to enhance productivity and streamline software delivery. This role requires a deep understanding of data engineering principles and the ability to work in a fast-paced environment, contributing to the development of scalable and efficient data pipelines for complex business problems.

Skills

MapReduce Hadoop Hive EMR Kafka Spark MySQL data modeling data warehousing Claude Code Github Copilot

What you'll do

Design and implement distributed data processing systems using tools like Hadoop and Spark.
Develop and optimize complex data models and data warehousing solutions.
Utilize AI-assisted coding tools to enhance software delivery efficiency.
Ensure high performance and scalability of enterprise data platforms.
Mentor junior engineers and provide technical guidance on data engineering projects.

What we're looking for

5+ years of experience with distributed data/computing tools like MapReduce, Hadoop, Hive, EMR, Kafka, Spark, and MySQL.
4+ years of experience in data modeling and data warehousing.
1+ year of experience using AI-assisted coding tools to enhance software delivery.
Bachelor’s or Master's Degree required.

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