Senior Data Engineer Platform & Pipeline Innovator (Remote)

Capital One; Helena (MT); Remote; USD 286,000 - 327,000; Full time

Job summary

Capital One is seeking a Senior Staff Data Engineer (Remote-Eligible) to lead data platform initiatives within Enterprise Data. You will drive scalable, governance-forward data pipelines and shareable data products across lines of business while mentoring engineers and shaping technical strategy.

You will work with AWS, Lakehouse architectures, Kafka, Flink, Spark, Snowflake, and Databricks to mature enterprise-scale systems, writing code in Python/SQL/Java/Scala as needed.

Qualifications

• Bachelor’s degree in Computer Science or a related quantitative field
• 9+ years of experience in data engineering
• 5+ years of experience in data architecture
• 3+ years of experience building applications in AWS
• 7+ years of programming experience (Python/Java/Scala)
• 6+ years of experience designing and developing data pipelines
• 4+ years of experience in data modeling and designing end-to-end data solutions

Responsibilities

• Build awareness and promote adoption of modern data technologies across the org
• Mentor engineers and recruit to grow Capital One Tech talent
• Lead engineering excellence and promote reuse of solutions
• Communicate with stakeholders across the enterprise
• Own end-to-end design and coding for critical data projects
• Influence architectural standards and scale team output
• Drive strategic direction for data engineering and emerging data/AI trends
• Align data systems and govern data flow across business units
• Create and socialize data strategy artifacts (governance, blueprints, roadmaps)

Skills

Python

SQL

Scala

Java

Data Pipelines

AWS

Spark

Snowflake

Databricks

Education

Bachelor's Degree in Computer Science or related field

Master's Degree (preferred)

Tools

EMR

Glue

Job description

Capital One is seeking a Senior Staff Data Engineer (Remote-Eligible) to lead data platform initiatives within Enterprise Data. You will drive scalable, governance-forward data pipelines and shareable data products across lines of business while mentoring engineers and shaping technical strategy.

You will work with AWS, Lakehouse architectures, Kafka, Flink, Spark, Snowflake, and Databricks to mature enterprise-scale systems, writing code in Python/SQL/Java/Scala as needed.