Senior Data Engineer — Microsoft Fabric Platform

Techwize

United States

Remote

USD 120,000 - 190,000

Full time

3 days ago
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Job summary

Techwize is seeking a Data Engineer to design, build, and maintain data solutions on Microsoft Fabric. You will own end-to-end development for the fundraising data platform, ingesting from Salesforce to a dimensional data warehouse and semantic models for reporting.

Responsibilities include building ingestion pipelines, implementing medallion architecture, and maintaining serve layers and semantic models with strong CI/CD practices and data security awareness.

Qualifications

  • 8+ years of data engineering experience on Microsoft Fabric platforms (Lakehouse, Warehouse, Pipelines, Notebooks, Dataflows Gen2).
  • Strong coding in PySpark, Spark SQL and T‑SQL.

Responsibilities

  • Build and maintain ingestion pipelines using Fabric Data Factory pipelines, Notebooks and Dataflows Gen2 for sources including Salesforce.
  • Implement the medallion architecture (Bronze, Silver, Gold) across Fabric Lakehouse and Warehouse.
  • Set up and maintain the serve layer – curated Gold tables, views and semantic models for reporting.

Skills

8+ years data engineering
PySpark
Spark SQL
T‑SQL
Power BI / Fabric semantic models
Medallion architecture
CI/CD (Git, Azure DevOps)
Fabric Data Factory pipelines
Data security (RLS/OLS)
Stakeholder communication
IT/CS/Data degree or equivalent

Education

Tertiary qualification in IT/Computer Science/Data or related field

Tools

Azure Synapse
Azure Data Factory
Databricks

Job description

Techwize is seeking a Data Engineer to design, build, and maintain data solutions on Microsoft Fabric. You will own end-to-end development for the fundraising data platform, ingesting from Salesforce to a dimensional data warehouse and semantic models for reporting.

Responsibilities include building ingestion pipelines, implementing medallion architecture, and maintaining serve layers and semantic models with strong CI/CD practices and data security awareness.

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