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Data Engineer MS Fabric

Flowserve • Manufacturing • Energy Efficiency • Python • SQL • Azure Data Factory • 1 month ago

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Salary

≈ $102k – $200k per year (Estimated)

Location

In office (Irving)

Seniority

Senior · 7+ years exp

Employment

Full-Time

Confirmed on the employer's own hiring board on Sep 28, 2026. First seen by Alion on Aug 21, 2026. Flowserve scores B on the Alion truth index.

Overview

Company

Impact

Profile match

Flowserve

Flowserve is an industrial flow control company headquartered in Irving, Texas, that designs, manufactures and services pumps, valves, mechanical seals, actuators and related equipment for the power, oil and gas, chemical, water and mining industries. Formed in 1997 through the merger of BW/IP and Durco International and listed on the New York Stock Exchange, it sells brands such as Byron Jackson, Durco, Worthington, Valtek, Limitorque and SIHI and employs more than 16,000 people in over 50 countries. It hires sales and applications engineers, manufacturing and controls engineers, machinists, assemblers and repair mechanics, cost accountants, planners and shared services staff.

flowserve.com • HQ: Irving, United States • Manufacturing • Energy Efficiency • Industrial Machinery • 1001-5000 employees • Est. 1997

Tech stack of Flowserve

Overview

We are looking for a Senior Data Engineer with strong 7-10 year hands-on experience in Azure and Microsoft Fabric to help modernize and migrate data products from Azure Synapse to Microsoft Fabric. The ideal candidate will have experience with Azure Data Factory, notebooks, Spark/PySpark, and building scalable data pipelines that support analytics and business reporting needs.

Responsibilities

Migrate existing data products, code, and workloads from Azure Synapse to Microsoft Fabric
Design, build, and support scalable data pipelines and data processing workflows
Develop and enhance data products that support business and analytics use cases
Build solutions using Azure Data Factory, notebooks, Spark/PySpark, SQL, and Python
Refactor pandas-based transformation logic into scalable PySpark and Python implementations
Work with structured and semi-structured data to enable downstream consumption
Implement full, delta, and CDC-based ingestion patterns from multiple data sources
Apply data warehousing concepts and medallion architecture principles in solution design
Validate migrated code and data outputs to ensure accuracy, consistency, and completeness
Perform data quality checks, performance tuning, monitoring, and issue resolution
Troubleshoot pipeline, code, and environment issues across Azure-based platforms
Collaborate with data analysts, engineers, and business stakeholders to gather requirements and deliver solutions
Document technical designs, migration approaches, and data product logic
Support code reviews, testing, release, and deployment activities

Required Technical Skills

7-10 years of strong hands-on experience with Microsoft Fabric and Azure fundamentals
Strong hands-on experience with Azure Synapse and Azure Data Factory
Strong hands-on experience with Spark and PySpark
Proficiency in Python and SQL
Experience with pandas and refactoring to PySpark/Spark-based implementations
Strong experience with Git and Azure DevOps, including pull requests, CI/CD, and deployment automation
Experience building reusable engineering patterns and shared libraries
Solid understanding of Azure storage, compute, security, and identity
Strong knowledge of data modeling, data transformation, and warehousing concepts
Experience with performance optimization and tuning

Technologies, Platforms, and Tools

Microsoft Fabric
Microsoft Azure Fundamentals
Azure Data Factory
Preferred knowledge on source systems such as SAP ECC, S/4 HANA, Oracle ERP, Salesforce
Worked with Delta, Parquet, JSON, and CSV file formats
Azure DevOps, Terraform

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