Senior Data Engineer

About CareScout Join us on a mission to simplify and dignify the aging experience. We are the children, siblings, neighbors, and friends of those navigating the fragmented and confusing system of long‑term care. Our team is ferociously curious and relentless in our pursuit of a better system – and we are deeply committed to a sense of belonging for all, in all phases of life. We’re creating a new experience for care seekers and their families, bringing together long‑term care options, non‑healthcare resources, education, and human support into one place. We work hard, we have fun, we care about each other, and we share the mission. If this sounds like a place where you could thrive, join us! CareScout is a wholly owned subsidiary of Genworth Financial, Inc, a Fortune 500 provider of products, services and solutions that help families address the financial challenges of aging. Position Title Senior Data Engineer Position Location This position is available to remote applicants residing in states/locations under Eastern Standard Time: Connecticut, Delaware, Florida, Georgia, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Tennessee, Vermont, Virginia, Washington DC, or West Virginia. About The Role We are seeking a highly skilled and experienced Senior 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. In this role, you will work closely with analysts, data scientists, ML/AI engineers, and product teams to design and deliver reliable, scalable data workflows on our Databricks Lakehouse platform. A successful candidate has strong engineering fundamentals, deep knowledge of modern data architectures, and experience transforming complex datasets into high‑quality, well‑modeled information that drives business impact. You’re comfortable owning end‑to‑end pipelines, improving data quality and reliability, and collaborating across teams. You thrive in environments where you can raise the bar on engineering excellence, build repeatable processes, and mentor others. What You’ll Do Data Pipeline Engineering 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. Lakehouse Modeling & Architecture 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. Data Quality & Observability 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. Collaboration & Cross‑Functional Support 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. Performance & Optimization Optimize Spark jobs, SQL queries, cluster configurations, and storage patterns for performance and cost. Improve reliability, reduce technical debt, and simplify complex pipelines. Security, Compliance & Governance Apply best practices for RBAC, data privacy, and PII handling using Unity Catalog. Ensure adherence to compliance frameworks and documentation standards. Continuous Learning Stay current on modern data engineering patterns, Lakehouse architecture, orchestration, and best practices. Explore new technologies that improve reliability, scalability, and developer productivity. What You Bring 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. Compensation The base salary pay range for this role starts at a minimum rate of $114,900 up to the maximum of $227,000. In addition to your base salary, you will also be eligible to participate in an incentive plan. The incentive plan is based on performance and the target earning opportunity is 15% of your base compensation. The final determination on base pay for this position will be based on multiple factors at the time of this job posting including but not limited to geographic location, experience, and qualifications to ensure pay equity within the organization. Employee Benefits & Well‑Being Genworth employees make a difference in people’s lives every day. We’re committed to making a difference in our employees’ lives. 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 #J-18808-Ljbffr