Senior Lead Data Engineer - Cloud, ML & Big Data

re-zoo-me; Richmond (VA); On-site; USD 209,000 - 262,000; Full time

Job summary

Capital One is hiring a Senior Lead Data Engineer to drive data engineering initiatives across the organization in a fast-paced, collaborative setting. You will lead teams building ML-enabled, distributed microservice architectures and cloud-based data warehousing solutions using Redshift, Snowflake, Hadoop, and Spark.

The role requires hands-on coding in Java/Scala/Python, deep experience with big data tech, and the ability to mentor others while delivering high-quality, scalable data platforms

Qualifications

• Bachelor’s degree required; advanced degree preferred.
• Minimum 6 years in application development; internship not counted.
• At least 2 years of big data technologies experience.
• At least 1 year of cloud computing experience (AWS/Azure/Google).
• Strong skills across Java, Scala, Python; ability to work in distributed systems.

Responsibilities

• Collaborate with cross-functional Agile teams to design, develop, test, implement, and support technical solutions.
• Lead a team of developers with expertise in ML, distributed microservices, and full-stack systems.
• Work with RDBMS and NoSQL databases, and cloud-based data warehousing (Redshift/Snowflake).
• Mentor team members, share tech trends, and engage with internal/external communities.
• Deliver cloud-based solutions that enable scalable experiences for millions of users.
• Perform unit tests and code reviews to ensure robust, performant software.

Skills

Big data tech

Cloud computing

Agile practices

Programming languages

Unix/Linux shell

NoSQL databases

Data warehousing

Streaming data

Mentoring

Education

Bachelor’s Degree

Master's Degree

Tools

Redshift

Snowflake

Hadoop

Kafka

Spark

MongoDB

Cassandra

Job description

Capital One is hiring a Senior Lead Data Engineer to drive data engineering initiatives across the organization in a fast-paced, collaborative setting. You will lead teams building ML-enabled, distributed microservice architectures and cloud-based data warehousing solutions using Redshift, Snowflake, Hadoop, and Spark.

The role requires hands-on coding in Java/Scala/Python, deep experience with big data tech, and the ability to mentor others while delivering high-quality, scalable data platforms