Senior Lead Data Engineer — Real-Time Platform Leader

Capital One; Plano (AL); On-site; USD 209,000 - 239,000; Full time

Job summary

Capital One is seeking a Senior Lead Data Engineer to design and build an enterprise streaming data platform that delivers timely insights. You’ll lead a team using Java, Scala, and Python to develop scalable data pipelines with Spark, Flink, Kafka, and cloud data warehouses like Snowflake and Redshift.

The role emphasizes collaboration within Agile teams, CI/CD, and security alignment, with opportunities to mentor engineers and influence data architecture in a complex, compliant environment.

Qualifications

• Bachelor’s Degree.
• 6+ years of experience in application development (Internship experience does not apply).
• 2+ years of experience in big data technologies.
• At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud).

Responsibilities

• Lead design and build enterprise-level scalable streaming data platform with low latency and fault tolerance.
• Build next-generation distributed streaming data pipelines and analytics data stores using Flink, Spark Streaming with Java, Scala, Python.
• Lead engineers building data pipelines with Spark, Flink, Kafka, Snowflake, AWS Big Data Services on large datasets.
• Collaborate with Agile teams to design, develop, test, implement and support technical solutions in full-stack tools and technologies.

Skills

Java

Scala

Python

Spark

Flink

Kafka

SQL

NoSQL

Education

Bachelor's Degree

Master's Degree

Tools

Snowflake

Redshift

AWS

Cloud Data Warehousing

Job description

Capital One is seeking a Senior Lead Data Engineer to design and build an enterprise streaming data platform that delivers timely insights. You’ll lead a team using Java, Scala, and Python to develop scalable data pipelines with Spark, Flink, Kafka, and cloud data warehouses like Snowflake and Redshift.

The role emphasizes collaboration within Agile teams, CI/CD, and security alignment, with opportunities to mentor engineers and influence data architecture in a complex, compliant environment.