Data Engineer - Techgroup America Inc.

We are seeking a highly skilled and motivated Senior Data Engineer to join our healthcare data engineering team. This role is focused on delivering high-quality, modern data solutions in a fast-paced, agile environment. You will work closely with engineering, analytics, data science, and product teams to build and maintain scalable data pipelines both on-prem and in the cloud.

This is a great opportunity to contribute to meaningful projects that directly impact how healthcare data is processed, interpreted, and delivered to improve patient outcomes and operational efficiency.

Must-Haves:

• 6+ years of experience working with SQL and relational database management systems

  4+ years of experience with Cloud technologies

  3+ years specifically with Microsoft SQL Server

  Strong familiarity with Azure

  Proficiency in programming and modifying code in languages like SQL, Python, and PySpark

  Experience supporting and implementing Cloud-based and on-prem data warehousing services

  Hands-on experience with:

  Dimensional data modeling, schema design, and data warehousing concepts

  Troubleshooting data issues and ensuring data quality

  Performance tuning and applying performance improvement techniques

  Strong analytical mindset with willingness to identify and implement process improvements and best practices

  Ability to take full ownership in a fast-paced, collaborative, team-based support environment

  Excellent oral and written communication skills

Nice to Haves / Plusses:

• Experience with Databricks

  Familiarity with healthcare data, especially healthcare insurance feeds such as Claims, Revenue, Rx, Medicare-specific files

Day-to-Day Responsibilities:

• Collaborate with data engineers, data scientists, analysts, and product teams to design and implement scalable data pipelines

  Process and transform healthcare data (e.g., claims, Rx, revenue, Medicare files) from 30+ payors into the enterprise data warehouse

  Support cloud migrations and modernization of existing on-premise data infrastructure

  Use SQL, Python, and PySpark to build efficient, reusable data workflows

  Ensure data quality, integrity, and performance

  Participate in troubleshooting, root cause analysis, and remediation of data-related issues

  Continuously evaluate and adopt emerging technologies and tools to enhance data capabilities

  Drive best practices in data architecture, coding standards, and development methodologies

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