Data Engineer 4 (Manager, IC)

Capital One Financial

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Quick summary

Work type: On-site
Location: Richmond, VA
Salary: $179,400–$204,700 / yr
Employment: Full-time
Posted: 7 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $173k

This role $192k

$125k $236k

below market most similar roles pay here above market

This role pays more than 52% of similar roles. Most pay $135,456–$211,200 — the blue band above. At the midpoint, this role pays about $192k versus about $173k 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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Data Engineer 4 (Manager, IC)

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The Data Engineer 4 (Manager, IC) joins the Enterprise Data Tech team to manage data technology, platforms, and experiences. This role involves designing, developing, and supporting technical solutions in a full-stack environment while influencing teams of developers, data analysts, and data scientists. You will independently build cloud-first data solutions, architect common engineering design patterns, and develop scalable data pipelines. Key responsibilities include implementing data security standards and ensuring operational efficiency across the data lifecycle. You will utilize Python, Spark, SQL, Java, and Scala alongside open-source relational and NoSQL databases. The role requires expertise in Databricks, Snowflake, and distributed microservices. You will solve complex problems related to lakehouse architecture, real-time streaming, and data observability to support the transition toward an AI-driven data ecosystem.

Skills

Python SQL Spark Scala Java Databricks Snowflake AWS Microsoft Azure Google Cloud NoSQL MongoDB Cassandra DynamoDB Redshift Airflow Dagster Splunk EMR Glue Agile Machine Learning Lakehouse Architecture

What you'll do

Design, develop, test, and support technical solutions using full-stack development tools and technologies.
Build and deliver world-class cloud data solutions and applications independently with minimal supervision.
Architect and enforce common data engineering design patterns to ensure code quality and reusability.
Design and build scalable, resilient data pipelines and platforms to handle increasing data volumes.
Implement data security standards, including encryption and fine-grained access control, to ensure regulatory compliance.
Utilize Python, Spark, and cloud-based data warehousing platforms like Databricks and Snowflake.
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 such as 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 relational and non-relational databases.
7+ years of experience in application development with proficiency in Python, SQL, Scala, or Java (preferred).

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