Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Chicago, IL
Salary: $179,400–$204,700 / yr
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $177k

This role $192k

$134k most similar roles pay here $220k

This role pays more than 57% of similar roles. Most pay $141,950–$211,200 — the shaded band above. At the midpoint, this role pays about $192k versus about $177k 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 1554 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 796 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Data Engineer Manager

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Data Engineer 4 (Manager, IC) joins a collaborative team to design, develop, test, and support technical solutions within an Agile environment. The role involves building robust cloud-first data solutions, architecting common engineering design patterns for code quality, and developing scalable pipelines that ensure performance under high volume. Responsibilities include mentoring others in the data community, ensuring data security standards like encryption and access control, and communicating complex technical concepts to stakeholders. The position requires proficiency in Python, Spark, SQL, Java, or Scala, alongside experience with NoSQL databases, Databricks, Snowflake, and tools like Airflow or Dagster. Candidates will work on distributed microservices and lakehouse architectures to solve complex business problems. The core work involves managing large-scale data infrastructure and creating reusable products within a cloud-based environment to support high-demand data platforms and pipelines.

Skills

Python SQL Spark Databricks Snowflake AWS Azure Scala Java NoSQL MongoDB Cassandra DynamoDB Redshift Airflow Dagster Splunk EMR Glue Agile

What you'll do

Design, develop, test, and implement technical solutions using full-stack development tools and technologies.
Build and deliver scalable, resilient cloud-first data solutions and applications independently.
Architect and enforce common data engineering design patterns to ensure code quality and reusability.
Develop data pipelines and platforms optimized for performance under high volume and business demands.
Implement data security standards including encryption and fine-grained access control to ensure regulatory compliance.
Influence a team of developers, analysts, and scientists by providing expertise in machine learning and lakehouse architecture.
Communicate technical concepts and data outcomes clearly to internal and external stakeholders to drive alignment.

What we're looking for

Bachelor's Degree or higher in Computer Science or a related quantitative field.
At least 4 years of experience in application development.
At least 2 years of experience in distributed data.
At least 2 years of experience with SQL.
At least 2 years of experience with one programming language (Python, Java, or Scala).
At least 2 years of experience in data pipeline design and development.
At least 1 year of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.
Experience with cloud platforms, distributed workloads, streaming pipelines, and NoSQL databases (preferred).

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