[Remote] Senior Data Engineer
Note: The job is a remote job and is open to candidates in USA. Genworth is a Fortune 500 provider of products and services that help families navigate the financial challenges of aging. They are seeking a Senior Data Engineer to build data pipelines, models, and infrastructure that support analytics and machine learning, collaborating with various teams to enhance data workflows and quality.
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 Gigflowx 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
Skills
- 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, Talensparkx 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
Benefits
- Competitive Compensation & Total Rewards Incentives
- Comprehensive Healthcare Coverage
- Multiple 401(k) Savings Plan Options
- Auto Enrollment in Employer-Directed Retirement Account Feature (100% employer-funded!)
- Generous Paid Time Off – Including 12 Paid Holidays, Volunteer Time Off and Paid Family Leave
- Disability, Life, and Long Term Care Insurance
- Tuition Reimbursement, Student Loan Repayment and Training & Certification Support
- Wellness support including gym membership reimbursement and Employee Assistance Program resources (work/life support, financial & legal management)
- Caregiver and Mental Health Support Services
Company Overview
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