Sr Data Engineer

Company Description

At Jack Link’s, we feed the journey. We take pride in rolling up our sleeves and getting things done together. Fueled by creativity, passion, and a commitment to doing things the right way, we tackle the hard stuff first and focus on real progress, bold moves, and no excuses. We create opportunities, celebrate wins, own our misses, and push forward as a team, knowing our strength comes from supporting one another and having fun along the way. We cultivate a workplace where passion meets purpose and our Team Members are inspired, recognized, and rewarded for their contributions. 

If you’re ready to make a difference and build something meaningful, we want you! 

Jack Link's Protein Snacks is a global leader in snacking and the No. 1 meat snack manufacturer worldwide. Headquartered in Minong, Wisconsin, Jack Link’s is strategically positioned with production, distribution, and support centers in key locations throughout North America, Brazil, Europe, and the Pacific Rim. This global network allows Jack Link's to deliver a wide variety of high-quality, great tasting protein snacks to consumers around the world. The company’s portfolio of brands includes Jack Link’s®, Lorissa’s Kitchen®, Wild River®, Golden Island®, Country Fresh Meats®, BiFi®, Peperami® , Mariani and Local Legends Meat Snacks.

Job Description

Are you ready to shape the future of data at Jack Link’s? We’re looking for a Senior Data Engineer to play a pivotal role in evolving our modern data foundation, enabling the next generation of analytics, automation, and insights. At Jack Link’s, we are building an analytics capability that fuels smarter decisions, faster innovation, and stronger business outcomes.

We’re looking for a Senior Data Engineer to lead the development of scalable, end-to-end data pipelines that power analytics, automation, and external product integrations. This full-stack role spans the entire data lifecycle—from ingestion and transformation to governance and infrastructure. A key focus area is building and maintaining scalable data pipelines from multiple data sources such as S/4HANA and Datasphere into Microsoft Fabric.

You’ll work closely with IT professionals, product owners, business relationship managers, and analytics teams to design and maintain data models, schemas, and tables that support reporting, dashboards, and ML/AI workflows. A strong focus will be on building and maintaining data pipelines; and data preparation and feature engineering to ensure data is structured, accessible, and optimized for decision-making. This role collaborates with enterprise data architects, platform engineers, and analytics product owners, and is ideal for someone who thrives in a cross-functional, product-oriented environment.

Core Responsibilities:

• Build & Manage Data Pipelines:
  Design and maintain scalable pipelines for ingesting, transforming, and storing data from SAP and non-SAP sources into Microsoft Fabric.
• Lead Medallion Architecture Design in Microsoft Fabric:
  Design and manage bronze, silver, and gold layer structures within Microsoft Fabric to support scalable, governed, and analytics-ready data pipelines.
• Develop in Microsoft Fabric:
  Use tools like Lakehouse, Data Warehouse, and Notebooks to process and transform data efficiently.
• Model & Prepare Data for Analytics:
  Build robust data models and perform feature engineering to support reporting, dashboards, and ML/AI use cases.
• Integrate SAP Systems:
  Connect SAP Datasphere and S/4HANA analytics into Fabric; orchestrate SAP and non-SAP data flows.
• Ensure Data Quality & Governance:
  Implement governance practices, maintain metadata, and ensure data integrity across platforms.
• Automate with Code:
  Write clean, efficient Python and SQL for ETL workflows, automation, and API development.
• Support MLOps & AIOps:
  Help deploy and monitor analytics models using modern DevOps practices.
• Collaborate & Mentor:
  Partner with business, analytics, and IT teams; mentor junior engineers and promote best practices.

Qualifications

Required Education:

• Bachelor’s degree in Information Technology, Computer Science, or related field or equivalent experience. 

Required Skills & Qualifications:

• 7+ years professional experience as data engineer
• Proven experience managing complex data pipelines and lakehouse architectures.
• Strong expertise in SQL, Python, and Spark.
• Deep understanding of data modeling, data architecture, and data governance.
• Familiarity