Sr. Data Engineer

Fuel Talent LLC; Seattle (WA); On-site; USD 103,320 - 117,096; Full time

Job summary

Fuel Talent LLC seeks a Senior Data Engineer to design and deliver cloud-native data platforms in Seattle. You will lead batch and real-time pipelines, build Lakehouse models, and govern data products for enterprise analytics and operations.

Ideal candidates bring 5–7+ years in data engineering, strong Azure and Fabric experience, and proficiency in Python, PySpark, SQL, and streaming design. Collaboration across teams and mentoring are key parts of this role.

Qualifications

• 5–7+ years of data engineering experience.
• Hands-on with Microsoft Fabric, Lakehouse, and Real-Time Analytics.
• Strong Azure experience including Data Factory, Databricks, Spark, Delta Lake.
• Proficient in Python and PySpark; SQL and data modeling skills.

Responsibilities

• Design and deliver cloud-native data platforms using Fabric and Azure.
• Lead scalable batch and real-time pipelines across bronze/silver/gold.
• Develop Lakehouse and medallion-architecture data models.
• Implement event-driven workflows and secure data practices.
• Mentor teammates and own CI/CD pipelines with Bitbucket/Git.

Skills

Microsoft Fabric

Azure

Lakehouse

Streaming

Apache Spark

Delta Lake

Python

PySpark

SQL

CI/CD

Git

Kafka

Azure Data Factory

Databricks

Synapse

Tools

Azure Data Factory

Databricks

Synapse

Kafka

Bitbucket Pipelines

Git

Job description

# Sr. Data EngineerApplyApplyPosted 5 days agoShareContractSeattle, Washington$75 Hourly**Senior Data Engineer** **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. |**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.