Data Engineering Lead & Platform Architect

Capital One; Cambridge (MA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking Data Engineers to transform data into cloud-first solutions that enable financial empowerment for millions of Americans. You’ll collaborate with agile teams, apply Python/Spark, and leverage Databricks and Snowflake to build scalable data pipelines.

You’ll mentor peers, design reusable patterns, and ensure data security and compliance. This role requires strong SQL and distributed data experience.

Qualifications

• Bachelor’s degree in Computer Science or related quantitative field
• At least 4 years of application development experience
• At least 2 years of distributed data experience
• At least 2 years of SQL experience
• At least 2 years of programming in Python, Java, or Scala
• At least 2 years of data pipeline design and development
• At least 1 year of data modeling for end-to-end data solutions using relational and non-relational databases

Responsibilities

• Collaborate with Agile teams to design, develop, test and support solutions
• Influence a team of developers, data analysts and data scientists
• Use Python, Spark and cloud data warehousing platforms like Databricks and Snowflake
• Mentor data community members and stay current with data trends
• Design scalable, cloud-first data solutions with high performance and security
• Architect common data engineering patterns for quality and reusability
• Communicate data outcomes clearly to stakeholders
• Build data pipelines with scalability and resilience in mind
• Enforce encryption and access controls to meet data privacy standards

Skills

SQL

Python

Scala/Java

Spark

Data pipelines

Education

Bachelor's degree in CS or related field

Statistics/Economics/OR Analytics background

Tools

Databricks

Snowflake

EMR

Airflow

Job description

Capital One is seeking Data Engineers to transform data into cloud-first solutions that enable financial empowerment for millions of Americans. You’ll collaborate with agile teams, apply Python/Spark, and leverage Databricks and Snowflake to build scalable data pipelines.

You’ll mentor peers, design reusable patterns, and ensure data security and compliance. This role requires strong SQL and distributed data experience.