Data Engineer: Microsoft Fabric & Data Pipelines

Tonic3; United States; Remote; USD 83,000 - 131,000; Part time

Job summary

Tonic3 is seeking a Data Engineer to design and optimize automated data pipelines on Microsoft Fabric and Azure for enterprise analytics. Youll build, validate, and orchestrate data flows, ensuring high quality datasets ready for Power BI dashboards.

The role emphasizes strong Python/PySpark skills, SQL mastery, and collaboration with architects and BI analysts to meet client reporting needs. Part-time, hourly engagement with US-based clients.

Qualifications

• Experience designing and deploying scalable ETL/ELT pipelines to ingest data from diverse sources.
• Hands-on expertise with Python or PySpark and SQL for data transformation and validation.
• Experience implementing Medallion Architecture (Bronze, Silver, Gold) for data lake housing.
• Strong communication skills to collaborate with clients and teams.

Responsibilities

• Design, build, and deploy scalable ETL/ELT pipelines to extract data from operational systems, REST APIs, databases, and flat files into the cloud.
• Medallion Architecture implementation to maintain Bronze, Silver, and Gold data layers.
• Develop and validate scripts using Python, PySpark, and SQL to ensure data quality and schema compliance.
• Model data for direct integration with Microsoft Power BI and enterprise dashboards.

Skills

ETL/ELT pipelines

Python

PySpark

SQL

Data modeling

Power BI

Microsoft Fabric

Azure

Data integration

REST APIs

Tools

Microsoft Fabric

Data Factory

Synapse Analytics

Azure Data Lake Storage

Power BI

Job description

Tonic3 is seeking a Data Engineer to design and optimize automated data pipelines on Microsoft Fabric and Azure for enterprise analytics. Youll build, validate, and orchestrate data flows, ensuring high quality datasets ready for Power BI dashboards.

The role emphasizes strong Python/PySpark skills, SQL mastery, and collaboration with architects and BI analysts to meet client reporting needs. Part-time, hourly engagement with US-based clients.