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Sr. Data Engineer
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Posted about 2 hours ago
Contract
Seattle, Washington
$75 Hourly
Senior Data Engineer
5–7+ years | Microsoft Fabric, Azure, Lakehouse, streaming, Spark
What you’ll do
Build cloud-native batch and streaming pipelines using Fabric Data Factory, Azure Data Factory, and Synapse.
Develop real-time data flows using Azure Event Hubs, Kafka, and Microsoft Fabric Real-Time Analytics.
Design Lakehouse, Warehouse, and medallion-architecture data models across bronze, silver, and gold layers.
Create event-driven workflows triggered by APIs, storage events, message streams, and serverless services.
Optimize Spark, Delta Lake, SQL, and streaming workloads for performance, reliability, and cost.
Implement governance, lineage, access controls, observability, and secure data-handling practices.
Establish reusable engineering patterns and mentor teammates on cloud data architecture and delivery.
Build and maintain CI/CD workflows through Bitbucket Pipelines and Git-based deployment practices.
What you’ll bring
5–7+ years of data engineering experience, including at least 3 years working in Azure or another major cloud platform.
Hands-on expertise with Microsoft Fabric, including Lakehouse, Warehouse, and Real-Time Analytics capabilities.
Strong experience with Azure Data Factory, Databricks, Apache Spark, and Delta Lake.
Proficiency in Python and PySpark; Scala experience is also valued.
Advanced SQL skills and experience tuning cloud-based data workloads.
Deep understanding of modern data architecture, dimensional modeling, medallion patterns, and streaming design.
Experience implementing CI/CD, automated testing, and Git-based release practices using Bitbucket.
Ability to communicate architectural decisions clearly and operate effectively in a distributed team.
Preferred qualifications
Advanced Fabric Warehouse implementation experience.
Experience developing serverless solutions with Azure Functions.
Hands-on experience with KQL and Fabric Real-Time Analytics.
Experience with enterprise data governance, lineage, cataloging, and regulated data environments.
5–7+ years | Microsoft Fabric, Azure, Lakehouse, streaming, Spark
| Role overview Design and deliver cloud-native data platforms using Microsoft Fabric and Azure. This senior engineer will lead the development of scalable batch and real-time pipelines, Lakehouse and medallion architectures, and governed data products that support enterprise analytics and operational use cases. |
Build cloud-native batch and streaming pipelines using Fabric Data Factory, Azure Data Factory, and Synapse.
Develop real-time data flows using Azure Event Hubs, Kafka, and Microsoft Fabric Real-Time Analytics.
Design Lakehouse, Warehouse, and medallion-architecture data models across bronze, silver, and gold layers.
Create event-driven workflows triggered by APIs, storage events, message streams, and serverless services.
Optimize Spark, Delta Lake, SQL, and streaming workloads for performance, reliability, and cost.
Implement governance, lineage, access controls, observability, and secure data-handling practices.
Establish reusable engineering patterns and mentor teammates on cloud data architecture and delivery.
Build and maintain CI/CD workflows through Bitbucket Pipelines and Git-based deployment practices.
What you’ll bring
5–7+ years of data engineering experience, including at least 3 years working in Azure or another major cloud platform.
Hands-on expertise with Microsoft Fabric, including Lakehouse, Warehouse, and Real-Time Analytics capabilities.
Strong experience with Azure Data Factory, Databricks, Apache Spark, and Delta Lake.
Proficiency in Python and PySpark; Scala experience is also valued.
Advanced SQL skills and experience tuning cloud-based data workloads.
Deep understanding of modern data architecture, dimensional modeling, medallion patterns, and streaming design.
Experience implementing CI/CD, automated testing, and Git-based release practices using Bitbucket.
Ability to communicate architectural decisions clearly and operate effectively in a distributed team.
Preferred qualifications
Advanced Fabric Warehouse implementation experience.
Experience developing serverless solutions with Azure Functions.
Hands-on experience with KQL and Fabric Real-Time Analytics.
Experience with enterprise data governance, lineage, cataloging, and regulated data environments.
