Lead Data Engineer, Data Transformation (Modeling and Architecture)

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Richmond, VAMcLean, VACambridge, MA
Employment: Full-time
Posted: 91 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $170k

$117k $223k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$212,250.

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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Lead Data Engineer, Data Transformation (Modeling and Architecture)

Role Posting Log in to save

The Lead Data Engineer - Data Transformation (Modeling and Architecture) joins a team of makers and disruptors to drive a major data transformation. This role involves building and maintaining comprehensive conceptual, logical, and physical data models to ensure scalable architecture and high data integrity across enterprise systems. You will architect robust data ecosystem solutions, including Data Lake and Data Warehouse patterns, while designing AI-ready architectures and high-performance pipelines. Key responsibilities include enforcing data governance standards, managing metadata frameworks, and translating technical concepts into business insights. The position requires proficiency in SQL, Spark, and Python, along with experience in cloud computing platforms like AWS, Microsoft Azure, or Google Cloud. You will also utilize distributed computing tools such as Hadoop, Kafka, and NoSQL implementations like Mongo or Cassandra.

Skills

Python SQL Spark AWS Microsoft Azure Google Cloud Scala Java Hadoop Hive Kafka Redshift Snowflake Cassandra MapReduce UNIX Linux Agile

What you'll do

Build and maintain comprehensive data models across conceptual, logical, and physical layers.
Lead the design of the organizational data landscape using Consumer Driven design principles.
Architect and implement robust data ecosystem solutions including Data Lake and Data Warehouse patterns.
Support high-performance data pipelines and complex transformations using SQL, Spark, and Python.
Define and enforce rigorous data governance standards and manage metadata frameworks.
Design AI-ready architectures to contribute to the evolution of the data ecosystem.
Deliver robust cloud-based solutions to drive digital product experiences.

What we're looking for

At least 4 years of experience in application development.
At least 2 years of experience in big data technologies.
At least 1 year of experience with cloud computing (AWS, Microsoft Azure, Google Cloud).
4+ years of experience in Data Architecture / Data Modeling (preferred).
7+ years of experience in application development including Python, SQL, Scala, or Java (preferred).
4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) (preferred).
4+ years of experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) (preferred).
Bachelor’s Degree.

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