Data Engineer 5, Senior Manager

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: New York, NYMcLean, VACambridge, MA
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 2 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $189k

This role $246k

$120k $278k

below market most similar roles pay here above market

This role pays more than 90% of similar roles. Most pay $135,675–$241,750 — the blue band above. At the midpoint, this role pays about $246k versus about $189k 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 2204 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1138 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Data Engineer 5, Senior Manager

Role Posting Log in to save

The Data Engineer 5 (Senior Manager, IC) joins the Enterprise Data Tech team to manage data technology, platforms, and experiences across the end-to-end data lifecycle. This role involves designing, developing, and supporting full-stack technical solutions, including scalable data pipelines and cloud-first data applications. You will architect common data engineering design patterns, lead large-scale transformative initiatives, and mentor developers, data analysts, and data scientists. Key responsibilities include evaluating platform choices and ensuring code quality for robust performance. You will utilize Python, Spark, SQL, Java, and Scala alongside open-source relational and NoSQL databases. The role requires expertise in distributed microservices, lakehouse architecture, and cloud-based data warehousing platforms like Databricks and Snowflake to solve complex business problems and evolve capabilities for the AI world.

Skills

Python Spark Databricks Snowflake AWS SQL Java Scala NoSQL MongoDB Cassandra DynamoDB Redshift EMR Glue Airflow Dagster Splunk Monte Carlo Agile Data Modeling Machine Learning Microservices Lakehouse Architecture

What you'll do

Design, develop, test, and implement 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.
Lead and execute large-scale, transformative data initiatives from end to end, including critical architectural decisions.
Mentor peers and junior engineers while providing technical leadership to data scientists and analysts.
Communicate technical concepts and data outcomes clearly to internal and external stakeholders to drive alignment.
Utilize Python, Spark, and cloud-based data warehousing platforms like Databricks and Snowflake.

What we're looking for

Bachelor's Degree or higher in Computer Science or a related quantitative field.
At least 6 years of experience in application development.
At least 4 years of experience in distributed data.
At least 4 years of experience with SQL.
At least 4 years of experience programming with Python, Java, or Scala.
At least 4 years of experience designing and developing data pipelines.
At least 2 years of experience in data modeling and designing end-to-end data solutions using relational and non-relational database systems.
Master’s Degree in Computer Science or a related field (preferred).
8+ years of experience in data engineering (preferred).
5+ years of hands-on experience designing, deploying and operating data workloads in AWS (preferred).
5+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks (preferred).
5+ years of experience designing, implementing, and operating real-time or streaming data pipelines (preferred).
5+ years of experience working with unstructured or semistructured data using NoSQL databases (preferred).
5+ years of experience designing and supporting data warehousing solutions (preferred).
4+ years of data modeling experience (preferred).
3+ years of experience working in an Agile development environment (preferred).
3+ years of experience developing user-centric reusable data products (preferred).
3+ years of experience working on data observability or data orchestration tools (preferred).

Save