Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: New York, NY
Salary: $215,200–$245,600 / yr
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $176k

This role $230k

$127k most similar roles pay here $258k

This role pays more than 88% of similar roles. Most pay $140,000–$211,200 — the shaded band above. At the midpoint, this role pays about $230k versus about $176k 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 936 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 933 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Data Engineer Manager

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As a Data Engineer 4 (Manager, IC), you will join a collaborative team to design, develop, and support technical solutions within an Agile environment. You will be responsible for building robust, cloud-first data pipelines and platforms that prioritize scalability, resilience, and operational efficiency while ensuring strict adherence to security standards like encryption and access control. The role involves architecting common engineering patterns to ensure code quality across various data platforms. You will work with Python, Spark, SQL, and Scala while utilizing tools such as Databricks, Snowflake, and NoSQL databases. Your daily work involves solving complex business problems by integrating emerging technologies into the infrastructure. You will also mentor others in the data community and serve as a technical ambassador to communicate outcomes clearly to stakeholders across the organization.

Skills

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

What you'll do

Design, develop, test, and support technical solutions using full-stack development tools and technologies.
Influence a team of developers, data analysts, and scientists in machine learning and lakehouse architecture.
Build and deliver cloud-first data solutions using Python, Spark, Databricks, and Snowflake.
Architect and enforce common data engineering design patterns to ensure code quality and reusability.
Design and build scalable, resilient data pipelines that perform under high volume and demand.
Implement data security standards including encryption and fine-grained access control for regulatory compliance.
Communicate technical concepts and data outcomes clearly to internal and external stakeholders.

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 solutions using relational and non-relational databases.
Experience with cloud platforms, distributed workloads, streaming pipelines, and data warehousing is preferred.

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