Lead Data Engineer, Data Transformation (Modeling and Architecture)

Capital One Financial

Confirmed live yesterday Low trust

Quick summary

Work type: On-site
Location: Richmond, VAMcLean, VACambridge, MA
Salary: $197,300–$225,100 / yr
Posted: 45 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $181k

This role $211k

$138k most similar roles pay here $234k

This role pays more than 74% of similar roles. Most pay $147,775–$214,150 — the shaded band above. At the midpoint, this role pays about $211k versus about $181k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

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View all roles at Capital One Financial

At a glance

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

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Lead Data Engineer - Data Transformation (Modeling and Architecture) joins the engineering team to drive major transformation within the enterprise data landscape. The role involves building and maintaining comprehensive conceptual, logical, and physical data models to ensure scalable architecture and high integrity across systems. You will architect robust data ecosystem solutions including Data Lake and Data Warehouse patterns while managing metadata frameworks and enforcing governance standards. Day-to-day responsibilities include developing high-performance pipelines and designing AI-ready architectures in collaboration with Agile teams. The role requires proficiency in SQL, Spark, Python, Scala, or Java, along with experience in big data technologies like Hadoop, Hive, Kafka, and NoSQL systems such as Mongo or Cassandra. Candidates should also possess skills in cloud computing platforms including AWS, Microsoft Azure, or Google Cloud to deliver robust cloud-based solutions for complex business problems.

Skills

Data Modeling Data Architecture SQL Spark Python AWS Microsoft Azure Google Cloud Scala Java Hadoop Hive EMR Kafka MySQL Cassandra Redshift Snowflake UNIX Linux Agile

What you'll do

Build and maintain comprehensive conceptual, logical, and physical data models for scalable architecture.
Design the organizational data landscape using Consumer Driven design principles to reflect business needs.
Architect and implement Data Lake and Data Warehouse solutions for analytical and operational requirements.
Develop high-performance data pipelines and complex transformations using SQL, Spark, and Python.
Define and enforce rigorous data governance standards and manage metadata frameworks for compliance.
Design AI-ready architectures to evolve the enterprise data ecosystem.
Translate complex technical concepts into actionable business insights for stakeholders.
Mentor other members of the engineering community on emerging technologies and best practices.

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, or Google Cloud).
4+ years of experience in Data Architecture and Data Modeling.
7+ years of experience in application development using Python, SQL, Scala, or Java.
4+ years of experience with distributed data/computing tools like Spark, Kafka, or Hadoop.
2+ years of experience with Agile engineering practices.
Work authorization that require immigration support from an employer.

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