Sr. Data Engineer - Remote

Sharecare•Atlanta, GA

21h•Remote

About The Position

Sharecare is a digital healthcare company that delivers software and tech-enabled services to stakeholders across the healthcare ecosystem to help improve care quality, drive better outcomes, and lower costs. Through its data-driven AI insights, evidence-based resources, and comprehensive platform – including benefits navigation, care management, home care resources, health information management, and more – Sharecare helps people easily and efficiently manage their healthcare and improve their well-being. Across its three business channels, Sharecare enables health plan sponsors, health systems and physician practices, and leading pharmaceutical brands to drive personalized and value-based care at scale. To learn more, visit www.sharecare.com. Job Summary: Sharecare is seeking a Senior Data Engineer to help build and evolve our next-generation data platform supporting high-profile partners and customers. In this role, you will collaborate closely with Product, Account Management, QA, Analytics, and Architecture teams to deliver scalable, reliable, and secure data solutions. This is a hands-on, high-impact position within a fast-paced, agile environment, offering the opportunity to develop breakthrough solutions in the health information and digital health space. The ideal candidate is self-driven, analytical, and detail-oriented, with deep expertise in Python-based data engineering, modern orchestration frameworks, and cloud-native architectures.

Requirements

Strong problem-solving and analytical thinking
Excellent communication and collaboration skills across technical and non-technical teams
Ability to work independently as well as within cross-functional, agile teams
Strong organizational and time-management skills
Ability to balance big-picture thinking with attention to technical detail
Flexibility and adaptability in a rapidly evolving environment
Bachelor’s degree (or higher) in Computer Science, Data Engineering, or a related field
10+ years of experience in data engineering or related roles
Strong proficiency in Python and related libraries (Pandas, SQLAlchemy, Boto3, Paramiko, Flask, FastAPI)
Advanced SQL skills with experience analyzing healthcare datasets (e.g., claims, provider directories)
Hands-on experience with orchestration tools such as Apache Airflow and Databricks Workflows
Strong experience with Apache Spark; exposure to Apache Flink is a plus
Experience integrating with .NET applications and working with SQL Server
Cloud platform experience (AWS, Azure, or GCP required)
Experience with data warehousing solutions such as Amazon Redshift or Vertica
Solid understanding of distributed systems and functional programming concepts
Proficiency with Git and modern CI/CD practices

Nice To Haves

Exposure to streaming technologies, containerization, and ML pipelines preferred
Familiarity with AI tools and large language models is a plus

Responsibilities

Design, build, and maintain scalable data pipelines using Python, Apache Airflow, and Apache Spark
Analyze business and technical requirements and translate them into reliable, future-proof data solutions
Develop, validate, deploy, and support complex ETL/ELT pipelines at scale
Build clean, secure, and maintainable REST APIs following company standards
Implement real-time and batch processing solutions for diverse data sources
Develop reusable data engineering and AI frameworks for enterprise-wide adoption
Define and manage domain-based “source of truth” data models, ensuring scalability and end-to-end data lineage
Implement data governance practices, automate data quality checks, and enable pipeline testing
Optimize data infrastructure for performance, cost efficiency, and reliability
Manage source control, CI/CD pipelines, and production deployments
Partner with data scientists and analysts to support AI/ML initiatives