Lead Data Engineer

Capital One Financial

Confirmed live 2 days ago Low trust

Quick summary

Work type: On-site
Location: Plano, TX
Salary: $179,400–$204,700 / yr
Posted: 89 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k

This role $192k

$141k most similar roles pay here $225k

This role pays more than 57% of similar roles. Most pay $149,106–$211,200 — the shaded band above. At the midpoint, this role pays about $192k versus about $180k 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

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Lead Data Engineer The Lead Data Engineer joins a collaborative team to design and build enterprise-level, scalable, low-latency, and fault-tolerant data platforms and processing applications. This role involves building next-generation governance controls, distributed data pipelines, and analytics data stores while influencing best practices for data architecture and the processing of both structured and unstructured data. The engineer will lead a group of developers to manage large datasets using big data technologies including Databricks, Snowflake, Spark, Kafka, Redshift, and AWS Big Data Services. Technical requirements include proficiency in Python, Java, TypeScript, React, SQL, Scala, and Unix/Linux shell scripting. Additionally, the role requires experience with NoSQL implementations like DynamoDB or OpenSearch, as well as cloud computing across AWS, Azure, or Google Cloud to deliver robust solutions for complex data-driven governance and analytics problems.

Skills

Python Java TypeScript React Databricks Snowflake Spark Kafka AWS Redshift SQL Scala Flink DynamoDB OpenSearch UNIX Linux CI/CD Agile Microservices

What you'll do

Design and build scalable, low-latency, and fault-tolerant enterprise data platforms and processing applications.
Develop next-generation data governance controls, distributed data pipelines, and analytics data stores using Python, Java, or TypeScript.
Lead a team of engineers in building data pipelines using Databricks, Snowflake, Spark, Kafka, and AWS services.
Establish best practices for data architecture and the processing of both structured and unstructured data.
Implement robust cloud-based solutions and full-stack technical systems to drive customer experiences.
Mentor other members of the engineering community and stay current on emerging technology trends.
Perform unit tests and conduct code reviews to ensure high performance and rigorous design standards.

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).
7+ years of experience in application development including Java, Python, SQL, or Scala.
4+ years of experience with distributed data computing tools like Flink, Kafka, and Spark.
4+ years of experience with NoSQL implementation, data warehousing (Redshift or Snowflake), and UNIX/Linux scripting.
2+ years of experience with Agile engineering practices.
Work authorization that require immigration support from an employer.

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