Lead Data Engineer - Data Publication and Transformation

Capital One Financial

Quick summary

Work type: On-site
Location: Richmond, VAMcLean, VA
Salary: $197,300–$225,100 / yr
Posted: 3 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $176k

This role $211k

$132k most similar roles pay here $235k

This role pays more than 79% of similar roles. Most pay $141,725–$211,200 — the shaded band above. At the midpoint, this role pays about $211k versus about $176k 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 794 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Lead Data Engineer - Data Publication and Transformation

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As a Lead Data Engineer at COPSSC, you will join a dynamic team focused on data publication and transformation. Your primary responsibilities include designing and implementing scalable data solutions using distributed computing tools such as Flink, Kafka, and Spark. You will work closely with cross-functional teams to build robust data pipelines and ensure seamless integration of various data sources into Snowflake or Redshift for efficient data warehousing. Additionally, you will leverage your expertise in Python, SQL, Golang, Java, and Scala to develop innovative solutions that address complex business challenges. This role requires a strong background in distributed systems, data warehousing, and hands-on experience with both relational and NoSQL databases.

Skills

Python SQL Golang Java Scala MapReduce Flink EMR Kafka Spark PostgreSQL DynamoDB Snowflake Redshift

What you'll do

Design and implement data transformation pipelines using distributed computing tools.
Optimize SQL queries and NoSQL implementations for efficient data retrieval.
Develop and maintain data warehousing solutions to support business intelligence needs.
Ensure data integrity and security throughout the data publication process.
Collaborate with stakeholders to understand data requirements and deliver scalable solutions.

What we're looking for

7+ years of experience in application development using Python, SQL, Golang, Java, or Scala.
4+ years of experience with distributed data/computing tools like MapReduce, Flink, EMR, Kafka, Spark, and MySQL.
4+ years of expertise in both SQL (PostgreSQL) and NoSQL (DynamoDB) implementations.
4+ years of hands-on experience in data warehousing technologies such as Snowflake or Redshift.
Bachelor’s Degree required.

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