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Über
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. Our four values guide our strategy, our decisions, and our interactions: Make it human. We care about the people that make up our customers, colleagues, and communities. Make it about others. We do what's best for our customers and collaborate to drive progress. Make it happen. We work with intention toward a common purpose and forge ways forward together. Make it better. We create fulfilling purpose-driven careers by learning from the world and each other. 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. *This role is not eligible for employment visa sponsorship* 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
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. 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. Additional Information
National Range: $120,900 - 187,000 High-Cost Range (includes New York): $151,100 - 234,000 Disclaimer: This role is aligned to a national market-based pay range. Actual compensation will vary based on geographic location, experience, skills, and other job-related factors. In addition to base salary, this role is eligible to participate in a bonus incentive plan. Incentive compensation is based on individual and company performance and is not guaranteed. 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
Sprachkenntnisse
- English
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