Senior Data Engineer Lead - Cloud & Data Pipelines

Capital One Group; Richmond (VA); Hybrid; USD 209,000 - 239,000; Full time

Benefits offered by this job

Health benefits

Competitive compensation

Job summary

Capital One is seeking Data Engineer 5 (Senior Manager, IC) to lead cloud-first data initiatives and collaborate with agile teams across the data stack. You will shape architecture, mentor engineers, and drive scalable data pipelines that empower millions of customers nationwide.

The role emphasizes partnership with product managers and software engineers, hands-on data engineering, and innovative use of technologies like Python, Spark, Databricks, and Snowflake. hybrid work is required.

Qualifications

• Bachelor's Degree or higher in Computer Science or related 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 in Python, Java, or Scala.
• At least 4 years of experience designing and developing data pipelines.
• At least 2 years in data modeling and end-to-end data solutions.

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support data solutions.
• Mentor other data professionals and influence engineers and data scientists.
• Build cloud-first data platforms for scalable, reliable data processing.
• Architect reusable data engineering design patterns across data platforms.
• Lead large-scale data initiatives end-to-end, evaluating platform choices.

Skills

SQL

Python

Spark

Data pipelines

Cloud data solutions

Education

Bachelor's degree

Master's degree

Tools

Databricks

Snowflake

Airflow

EMR

Job description

Capital One is seeking Data Engineer 5 (Senior Manager, IC) to lead cloud-first data initiatives and collaborate with agile teams across the data stack. You will shape architecture, mentor engineers, and drive scalable data pipelines that empower millions of customers nationwide.

The role emphasizes partnership with product managers and software engineers, hands-on data engineering, and innovative use of technologies like Python, Spark, Databricks, and Snowflake. hybrid work is required.