Data Engineer: Azure, Databricks & Fabric Pipelines

MAXhealth

Tampa (FL)

Hybrid

USD 100,000 - 140,000

Full time

14 days+
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Job summary

MaxHealth is seeking a Data Engineer to develop, maintain, and support enterprise data pipelines within its cloud-based analytics ecosystem. You will collaborate with Data Platform Engineers, Data Analysts, and business stakeholders to ensure timely, accurate data for reporting and decision-making.

You will modernize legacy processes, build ADF pipelines, and monitor data quality across the data lake and warehouses, while supporting Fabric initiatives and Azure tools.

Qualifications

  • 4+ years in data engineering or related roles.
  • Experience with SQL Server and strong SQL skills.
  • Hands-on experience with Azure Data Factory, SSIS or similar tools.
  • Experience developing ETL/ELT processes and data transformations.
  • Scripting experience with Python, PowerShell or similar languages.
  • Understanding of relational databases and data modeling.

Responsibilities

  • Develop and maintain data pipelines using ADF, Databricks, and Fabric.
  • Migrate legacy SSIS processes to modern cloud-based solutions.
  • Build reusable ELT processes for ingestion and transformation.
  • Integrate data from operational systems, apps, APIs, and vendors.
  • Support data loading into data lake, warehouse, and reporting environments.
  • Monitor pipelines and troubleshoot failures.
  • Document data mappings and transformation logic.

Skills

SQL development
Python scripting
Data modeling
ETL/ELT concepts
Analytical thinking
Team collaboration

Tools

Azure Data Factory (ADF)
SSIS
Databricks
Fabric
Azure DevOps

Job description

MaxHealth is seeking a Data Engineer to develop, maintain, and support enterprise data pipelines within its cloud-based analytics ecosystem. You will collaborate with Data Platform Engineers, Data Analysts, and business stakeholders to ensure timely, accurate data for reporting and decision-making.

You will modernize legacy processes, build ADF pipelines, and monitor data quality across the data lake and warehouses, while supporting Fabric initiatives and Azure tools.

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