Lead Data Engineer (Bank Tech)

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VA
Salary: $197,300–$225,100 / yr
Posted: 4 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k

This role $211k

$145k most similar roles pay here $234k

This role pays more than 69% of similar roles. Most pay $153,412–$220,900 — the shaded band above. At the midpoint, this role pays about $211k versus about $187k 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 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Lead Data Engineer (Bank Tech)

Apply Now Log in to save

As a Lead Data Engineer at Bank Tech, you will join a dynamic team focused on advancing the company's data infrastructure. Your primary responsibilities include designing and implementing robust data pipelines, ensuring high-quality data governance, and collaborating with cross-functional teams to drive innovative solutions. Day-to-day tasks involve working with large datasets, developing scalable ETL processes, and integrating various data sources to support business intelligence initiatives. The role requires expertise in Python, SQL, and cloud platforms like AWS or Azure. Additionally, experience with big data technologies such as Hadoop and Spark is essential. This position plays a crucial role in addressing complex financial data challenges at scale, ensuring that the organization can leverage its vast data assets effectively to inform strategic decisions.

Skills

Python SQL AWS Kubernetes Docker CI/CD Git PostgreSQL Snowflake BigQuery Hadoop Spark Data Warehousing ETL Agile

What you'll do

Design and implement data architecture solutions to support business needs.
Optimize data processing workflows to enhance efficiency and scalability.
Ensure data security and compliance with regulatory standards.
Develop ETL processes to integrate diverse data sources effectively.
Mentor junior engineers and provide technical guidance on projects.

What we're looking for

Bachelor’s degree in Computer Science, Engineering, or related field.
Proven experience leading data engineering teams and projects.
Expertise in designing and implementing large-scale data architectures.
Strong knowledge of cloud platforms (AWS, Azure, GCP) for data solutions.
Experience with big data technologies such as Hadoop, Spark, Kafka.
Excellent problem-solving skills and ability to work under pressure.

Save