Data Engineer

Carenet Health

116d

About The Position

The Data Engineer at Carenet Health is responsible for building and maintaining the data solutions that power our business intelligence and analytics initiatives. This role focuses on designing reliable data pipelines, integrating data from multiple sources, and ensuring accuracy, security, and accessibility across our enterprise data platforms. By transforming raw information into structured, high-quality datasets, the Data Engineer enables teams across Carenet Health to make informed, data-driven decisions that improve healthcare experiences and outcomes.

Requirements

• 5+ years of experience as a Data Engineer, preferably with cloud-based data platforms (Azure strongly preferred).
• Advanced SQL expertise with a proven ability to optimize complex queries.
• Hands-on experience with Azure data services: Databricks, ADF, ADLS, Azure SQL; familiarity with Event Hub or Synapse is a plus.
• Knowledge of Medallion / Lakehouse architecture (bronze, silver, gold layers).
• Strong background in relational data modeling and data warehousing (dimensions, facts, star schemas).
• Experience with big data and distributed processing (Spark, Databricks, Delta Lake); exposure to Snowflake or Fabric a plus.
• Experience with CI/CD and version control (GitHub, Azure DevOps) for data pipelines.
• Familiarity with data security, privacy best practices, and compliance frameworks.
• Knowledge of NoSQL databases (document store, key-value).
• Proficiency in Python (PySpark preferred); additional languages such as C#, R, or JavaScript are beneficial.
• Excellent communication and collaboration skills to partner across technical and business teams.
• Strong organizational skills, attention to detail, and ability to manage multiple priorities in a fast-paced environment.
• Energetic, adaptable, and committed to continuous learning and improvement.

Responsibilities

• Partner with BI teams, analysts, and business stakeholders to design, build, and maintain Carenet Health’s enterprise data warehouse.
• Ingest and integrate data from both on-premises and cloud-based systems.
• Build, monitor, maintain, and troubleshoot complex data pipelines.
• Provision and manage infrastructure to support scalable and cost-effective data operations.
• Design and implement data marts, including DDL generation.
• Optimize data architectures for performance, security, and cost efficiency.
• Analyze raw data and create structured datasets for analytics and reporting.
• Enhance data quality, consistency, and efficiency through automation and best practices.
• Provide technical leadership in discussions around pipeline design, optimization, and implementation.

Benefits

• Opportunities for professional growth.
• Focus on work-life balance.

What This Job Offers

• Career Level: Mid Level