Data Engineer
Peter Millar Durham, North Carolina, United States
Retail Apparel and Fashion · 201-500 employees
About the role
The Data Engineer will design, build, and maintain scalable ETL/ELT pipelines and data platform solutions using Microsoft Fabric and Azure technologies. This role involves collaborating with cross-functional teams to ensure high-quality data availability for reporting, analytics, and business operations.
What they look for
Requirements
Candidates must have a bachelor's degree in a technical field and 3–5 years of hands-on experience in data engineering. Proficiency in SQL, Python or PowerShell, and Azure data services is required, along with strong problem-solving and communication skills.
Full description
It's fun to work in a company where people truly BELIEVE in what they're doing!
We're committed to bringing passion and customer focus to the business.
Peter Millar was founded in 2001 with a single cashmere sweater offered in 24 colors. Based in Raleigh and Durham, North Carolina, the American lifestyle brand has grown to include luxury performance sportswear, seasonal resort and country club apparel, sophisticated classics, casually refined tailored clothing and sartorial accessories.
We strive to capture timeless style upgraded with signature innovations, in designs that are in tune with modern life. We embrace working hard, being kind and doing right by our customers, aiming to set a higher standard for the apparel industry.
We are seeking a Data Engineer to design, build, and support modern data pipelines and data platform solutions using Microsoft and cloud-based technologies. This role will be responsible for developing and optimizing scalable data pipelines, supporting the Microsoft Fabric platform, and ensuring high-quality, reliable data is available for reporting, analytics, and business operations.
The ideal candidate has strong experience with SQL, Azure data services, and ETL/ELT development, and is comfortable working across both pipeline development and data platform responsibilities.
ESSENTIAL FUNCTIONS:
- Design, build, and maintain ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric Data Factory, and Dataflows.
- Develop and optimize data ingestion workflows across structured and semi-structured data sources.
- Troubleshoot pipeline failures, data issues, and performance bottlenecks to ensure reliable data delivery.
- Support and maintain data platform components within Microsoft Fabric, including Lakehouse, Warehouse, and OneLake.
- Work with medallion architecture (bronze, silver, gold) to structure and manage data transformations.
- Contribute to Spark and notebook-based data processing for large-scale data transformation.
- Monitor data pipelines and platform health, and support alerting and incident response processes.
- Perform data validation, profiling, and cleansing to ensure high-quality and accurate data.
- Work with business stakeholders to gather data requirements and translate them into technical solutions.
- Collaborate with analysts, data scientists, and application teams to support reporting and downstream use cases.
- Write and maintain documentation for data pipelines, transformations, and workflows.
- Participate in code reviews and contribute to CI/CD and DevOps practices using Git/GitHub.
- Follow and help enforce data governance, security, and best practices across the data platform.
COMPETENCIES / EDUCATION / EXPERIENCE:
- Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field (or equivalent experience).
- 3–5 years of hands-on experience in data engineering or a related technical role.
- Strong SQL skills, including query optimization, indexing, and performance tuning.
- Proficiency in Python and/or PowerShell for data transformation and automation.
- Hands-on experience with Azure data services, including Data Factory, Synapse Analytics, Azure SQL, and Data Lake Storage.
- Working experience with Microsoft Fabric, including Lakehouse, Dataflows, and pipelines.
- Solid understanding of ETL/ELT design patterns and data pipeline best practices.
- Experience working with structured and semi-structured data formats (JSON, XML, etc.).
- Familiarity with source control tools such as Git/GitHub and CI/CD practices.
- Strong analytical, problem-solving, and communication skills.
PREFERRED SKILLS:
- Experience with Spark (PySpark) for large-scale data processing.
- Familiarity with Delta Lake and Parquet data formats.
- Exposure to Power BI or other data visualization tools.
- Experience with APIs, including development and integration.
- Microsoft Fabric certification (DP-600) or interest in pursuing certification.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
Peter Millar & G/FORE are equal opportunity employers. In accordance with anti-discrimination law, it is the purpose of this policy to effectuate these principles and mandates. Both Peter Millar & G/FORE prohibit discrimination and harassment of any type and they afford equal employment opportunities to employees and applicants without regard to race, color, religion, gender, age, national origin, genetic information, marital status, disability status, protected veteran status, sexual orientation, or any other characteristic protected by law. Both Peter Millar & G/FORE comply with applicable state, county and local laws governing non-discrimination in employment.
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