Lead Data Engineer

Genworth Financial is a Fortune 500 provider of products, services, and solutions that help families address the financial challenges of aging. We are seeking a highly skilled and experienced Lead Data Engineer to join our growing data and machine learning organization and help build the pipelines, models, and infrastructure that power our analytics, machine learning, and operational data needs.

Responsibilities:

• Design, build, and maintain scalable ETL/ELT pipelines using Spark, Python, SQL, and Databricks
• Implement reliable ingestion frameworks for batch and streaming data sources
• Ensure pipelines meet SLAs, data quality standards, and production-grade reliability
• Develop robust data models across raw, curated, and semantic layers using Delta Lake
• Create dimensional models, star schemas, and domain-layer datasets for analytics and ML
• Establish and maintain standards for schema design, metadata, and lineage
• Implement data validation, anomaly detection, SLAs, and documentation across pipelines
• Build automated tests, monitoring, and alerting for freshness, completeness, and accuracy
• Partner with platform teams to enhance observability and operational tooling
• Work closely with analysts to understand business KPIs and deliver high-quality curated datasets
• Partner with ML engineers and data scientists to build reusable feature pipelines
• Collaborate with data platform engineers to optimize compute, governance, and orchestration
• Optimize Spark jobs, SQL queries, cluster configurations, and storage patterns for performance and cost
• Improve reliability, reduce technical debt, and simplify complex pipelines
• Apply best practices for RBAC, data privacy, and PII handling using Unity Catalog
• Ensure adherence to compliance frameworks and documentation standards
• Stay current on modern data engineering patterns, Lakehouse architecture, orchestration, and best practices
• Explore new technologies that improve reliability, scalability, and developer productivity

Requirements:

• 7+ years of experience in data engineering or related roles
• Strong expertise with Python, SQL, Spark, and distributed data processing
• Hands-on experience with Databricks, Delta Lake, and Lakehouse architectures
• Deep understanding of ETL/ELT design, data modeling, and data quality practices
• Experience building scalable, production-grade data pipelines
• Experience collaborating with analytics, ML, and product teams
• Strong communication skills with the ability to clarify data requirements and explain technical decisions