Lead Data Engineer - Data Transformation (Modeling and Architecture)

Overview

Lead Data Engineer - Data Transformation (Modeling and Architecture)

Experience Level

Manager

Primary Address

Richmond, Virginia

Qualifications

• Bachelor’s Degree
• At least 4 years of experience in application development
• At least 2 years of experience in big data technologies
• At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

Preferred Qualifications

• 4+ years of experience in Data Architecture / Data Modeling
• 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
• 4+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
• 4+ year experience working on real-time data and streaming applications
• 4+ years of experience with NoSQL implementation (Mongo, Cassandra)
• 4+ years of data warehousing experience (Redshift or Snowflake)
• 4+ years of experience with UNIX/Linux including basic commands and shell scripting
• 2+ years of experience with Agile engineering practices
• Experience leveraging interactive AI tooling to accelerate productivity

Responsibilities

• Build and maintain comprehensive data models—spanning conceptual, logical, and physical layers—to ensure scalable architecture and high data integrity across enterprise systems.
• Lead design of the org data landscape by applying Consumer Driven design principles, ensuring that data structures reflect business realities and evolving organizational needs.
• Arcitect and implement robust data ecosystem solutions, including Data Lake and Data Warehouse patterns, to support diverse analytical and operational requirements.
• Support high-performance data pipelines and complex transformations that utilize SQL, Spark, and Python to process large-scale datasets efficiently.
• Define and Enforce rigorous data governance standards while managing metadata frameworks to ensure data compliance and discoverability.
• Translate complex technical concepts into actionable business insights, working independently to lead initiatives and collaborate with stakeholders to meet organizational goals.
• Contribute to the evolution of the data ecosystem by designing AI-ready architectures.
• Collaborate with and across Agile teams to design, develop, implement, and support technical solutions.
• Work with a team of developers with deep experience in machine learning, AI, distributed microservices, and full stack systems.
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community.
• Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment.