Data Engineer
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Job Location:
Seattle, OR - USA
Monthly Salary:
Not Disclosed
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
Job Role: Senior Data Engineer
Location: Remote
JD:
Key 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 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.
Required Qualifications
5 years of experience in data engineering with a focus on Microsoft Azure and Fabric technologies.
Strong expertise in:
o Microsoft Fabric (Lakehouse Dataflows Gen2 Pipelines Notebooks)
o Azure Data Factory Azure SQL Azure Data Lake Storage Gen2
o Power BI and/or other visualization tools
o Azure Functions Logic Apps and orchestration frameworks
o SQL Python and PySpark/Scala
Experience working with structured and semi-structured data (JSON XML CSV Parquet).
Proven ability to build metadata-driven architectures and reusable components.
Familiarity with agent-based architectures and conversational AI integration is a plus.
Strong understanding of data modeling data governance and security best practices.
Preferred Qualifications
Experience with Azure OpenAI Copilot Studio or similar conversational platforms.
Knowledge of CI/CD pipelines and DevOps practices for data engineering.
Experience in building multi-tenant data platforms or domain-specific lakes.
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 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.
Required Qualifications
5 years of experience in data engineering with a focus on Microsoft Azure and Fabric technologies.
Strong expertise in:
o Microsoft Fabric (Lakehouse Dataflows Gen2 Pipelines Notebooks)
o Azure Data Factory Azure SQL Azure Data Lake Storage Gen2
o Power BI and/or other visualization tools
o Azure Functions Logic Apps and orchestration frameworks
o SQL Python and PySpark/Scala
Experience working with structured and semi-structured data (JSON XML CSV Parquet).
Proven ability to build metadata-driven architectures and reusable components.
Familiarity with agent-based architectures and conversational AI integration is a plus.
Strong understanding of data modeling data governance and security best practices.
Preferred Qualifications
Experience with Azure OpenAI Copilot Studio or similar conversational platforms.
Knowledge of CI/CD pipelines and DevOps practices for data engineering.
Experience in building multi-tenant data platforms or domain-specific lakes.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
