Lead Data Engineer

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: Plano, TX
Employment: Full-time
Posted: 134 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 $164k

$118k $211k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $126,800–$202,200.

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

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JOB TITLE: Lead Data Engineer The Lead Data Engineer joins a team of makers and disruptors to design and build enterprise-level, scalable, and fault-tolerant data platforms. This role involves leading a group of engineers to develop next-generation data-driven governance controls, distributed data pipelines, and analytics data stores. Day-to-day responsibilities include influencing best practices for data architecture, processing structured and unstructured data, and collaborating across agile teams to deliver robust cloud-based solutions. The position requires proficiency in Python, Java, Typescript, React, SQL, and Scala. Key technologies include Databricks, Snowflake, Spark, Kafka, AWS Big Data Services, Redshift, Flink, DynamoDB, and OpenSearch. The work focuses on solving complex business problems by creating low-latency data processing applications and high-performance systems within a full-stack development environment.

Skills

Python Java SQL Scala TypeScript React Databricks Snowflake Spark Kafka AWS Microsoft Azure Google Cloud Redshift Flink DynamoDB OpenSearch UNIX Linux CI/CD Agile Machine Learning Microservices

What you'll do

Design and build scalable, low-latency, and fault-tolerant enterprise data platforms and processing applications.
Build next-generation data governance controls, distributed data pipelines, and analytics data stores using Python, Java, and TypeScript.
Lead a team of engineers in developing big data pipelines using Databricks, Snowflake, Spark, and Kafka.
Influence best practices for data architecture and the processing of structured and unstructured data.
Develop and support robust cloud-based solutions in a full-stack development environment.
Perform unit tests and conduct code reviews to ensure performance tuning and rigorous design.
Mentor other members of the engineering community and share expertise on emerging technology trends.

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).
7+ years of experience in application development including Java, Python, SQL, or Scala (preferred).
4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud) (preferred).
4+ years of experience with Distributed data computing tools (Flink, Kafka, Spark) (preferred).
4+ years of experience with real-time data and streaming applications (preferred).
Bachelor’s Degree.

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