Senior Data Engineer

Genworth Financial

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$114,900–$114,900 / yr
Posted
40 days ago
Closes
Jun 29, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $179k
This role $115k
$102k most similar roles pay here $234k

This role pays less than 94% of similar roles. Most pay $146,287–$211,200 — the shaded band above. At the midpoint, this role pays about $115k versus about $179k for comparable roles.

Based on 240 similar postings.

Employer

About Genworth Financial

Genworth Financial is a financial services company focused on mortgage insurance, long-term care insurance, and life insurance and annuity products to help people protect their financial well-being. Industry: Insurance & Financial Services

Genworth Financial currently has 15 open roles on FindRole.

Listed pay typically runs $114,900–$114,900 across 8 roles with salary data.

Most-posted roles

View all roles at Genworth Financial

At a glance

TL;DR · Senior Data Engineer

As a Senior Data Engineer at CareScout, you will join our dynamic data and machine learning team to design and implement robust data workflows using Databricks Lakehouse platform. Your day-to-day responsibilities include building scalable ETL/ELT pipelines with Spark, Python, and SQL, ensuring high-quality data models across various layers, and maintaining strict data quality standards. You will collaborate closely with analysts, data scientists, ML engineers, and product teams to deliver reliable data solutions that drive business impact. Key skills required are proficiency in Python, SQL, Spark, Databricks, Delta Lake, and experience with ETL/ELT design, data modeling, and governance practices. This role involves optimizing performance, ensuring security compliance, and fostering a culture of continuous learning within the fast-growing healthcare technology sector.

What you'll do

  • Design, build, and maintain scalable ETL/ELT pipelines using Spark, Python, SQL, and Databricks.
  • Develop robust data models across raw, curated, and semantic layers using Delta Lake.
  • Implement data validation, anomaly detection, SLAs, and documentation across pipelines.
  • Optimize Spark jobs, SQL queries, cluster configurations, and storage patterns for performance and cost.
  • Apply best practices for RBAC, data privacy, and PII handling using Unity Catalog.
  • Collaborate with ML engineers to build reusable feature pipelines.
  • Stay current on modern data engineering patterns, Lakehouse architecture, orchestration, and best practices.

What we're looking for

  • 7+ years experience in data engineering or related roles
  • 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
  • Proven ability to collaborate effectively across analytics, ML, and product teams
  • Strong communication skills for clarifying requirements and explaining technical decisions

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