Data Engineer

Overview

Lead a team in research and implementation of complex data engineering projects, including multiple data models, maps, and workflows. Act as primary contact for the team, managing prioritization and execution of tasks. Serve as Subject Matter Expert (SME), deeply understanding the data, its structure, and business context. Design, develop, and deliver robust end-to-end data integration solutions following Data Engineering best practices and test-driven development.

Translate technical requirements into effective, scalable code solutions. Develop new ETL/ELT pipelines between various source and target systems. Perform unit testing to ensure data accuracy and system reliability. Develop and optimize data models using industry-standard techniques (e.g., slowly changing dimensions, star schemas, data vault). Apply data warehousing concepts, including Kimball and Inmon methodologies, DDS, ODS, and data flow from source systems to BI tools.

Utilize advanced SQL skills, including DDL/DML operations, normalization, relational data modeling, ACID transactions, and performance/security best practices. Exhibit strong experience with Snowflake and Azure Cloud technologies. Act independently as a self-starter, proactively identifying and solving problems. Healthcare industry experience required. Strong communication skills (rated 9/10). Remote work for candidates in EST or CST time zones.

• Mid-Senior level

• Contract

• Information Technology

• Wellness and Fitness Services
• Hospitals and Health Care
• Mental Health Care