Lead Data Engineer (Enterprise Platforms Technology) ( Java, Python, Scala, AWS)

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

$153k most similar roles pay here $233k

This role pays more than 75% of similar roles. Most pay $160,962–$214,950 — 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 798 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 791 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead Data Engineer (Enterprise Platforms Technology) ( Java, Python, Scala, AWS)

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As a Lead Data Engineer on the Enterprise Platforms Technology team, you will oversee the design and implementation of scalable data solutions using Java, Python, and Scala. Your day-to-day responsibilities include managing distributed computing tools such as MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, and MySQL to process large datasets efficiently. You will work on complex business problems requiring advanced analytics and machine learning capabilities, ensuring that data pipelines are optimized for performance and reliability. This role demands a deep understanding of cloud technologies like AWS, as well as strong leadership skills to mentor junior engineers and drive innovation within the team.

Skills

Java Python Scala AWS Hadoop Hive EMR Kafka Spark MySQL

What you'll do

Design and implement large-scale data processing systems using distributed computing tools.
Optimize data pipelines for efficiency and scalability on AWS infrastructure.
Develop and maintain ETL processes to integrate diverse data sources.
Ensure data quality and integrity through rigorous testing and validation.
Collaborate with stakeholders to understand data requirements and deliver solutions.

What we're looking for

4+ years of experience with distributed data and computing tools.
Strong proficiency in Java, Python, and Scala programming languages.
Extensive knowledge of AWS services and platforms.
Bachelor’s Degree required.
Experience with MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL.

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