ETL Data Platform Engineer - Azure Fabric & Lakehouse

Robotic Technologies Automation; Redmond (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

ROBOTIC PROCESS AUTOMATION LLC in Redmond, WA is seeking a senior data engineer to design and implement ETL pipelines using Microsoft Fabric and Azure Data Factory, building a metadata-driven Lakehouse to support multiple consumption patterns.

You will develop agent-specific data lakes and an orchestration layer to answer customer questions across agents, enabling interactive data consumption via Power BI and Azure OpenAI.

Qualifications

• 7+ years of experience in data engineering focusing on Microsoft Azure Data stack and Fabric technologies.
• Strong expertise in executive written and oral communication.
• Familiar with agent-based architectures and conversational AI integration is a plus.
• Strong understanding of data governance and security best practices.

Responsibilities

• Design and implement ETL pipelines using Microsoft Fabric (Dataflows, Pipelines, Lakehouse ,warehouse, sql) and Azure Data Factory.
• Build and maintain a metadata driven Lakehouse architecture with threaded datasets to support multiple consumption patterns.
• Develop agent specific data lakes and an orchestration layer for an uber agent that can query across agents to answer customer questions.
• Enable interactive data consumption via Power BI, Azure OpenAI, and other analytics and AI tools.
• Ensure data quality, lineage, and governance across all ingestion and transformation processes.
• Collaborate with product teams to understand data needs and deliver scalable solutions.
• Optimize performance and cost across storage and compute layers.

Skills

Azure Data Stack

Fabric Lakehouse

Data Factory

Azure SQL

Power BI

Python

PySpark

Data Modeling

Data Governance

Security Best Practices

Tools

Azure Data Factory

Azure Data Lake Gen2

Azure SQL

Job description

ROBOTIC PROCESS AUTOMATION LLC in Redmond, WA is seeking a senior data engineer to design and implement ETL pipelines using Microsoft Fabric and Azure Data Factory, building a metadata-driven Lakehouse to support multiple consumption patterns.

You will develop agent-specific data lakes and an orchestration layer to answer customer questions across agents, enabling interactive data consumption via Power BI and Azure OpenAI.