Sr Data Engineer

About Link Snacks

At Link Snacks
, we show up hungry, roll up our sleeves, plaid or otherwise, and dive straight into the hard work. We don’t hide from challenges; we hunt them down. We push harder, move faster, and take the kinds of big swings that built this business in the North Woods of Wisconsin four decades ago.

We’re everyday people who deliver extraordinary results. Innovation, creativity, and urgency aren’t buzzwords, they’re expectations. And just like the real protein snacks we make across our global house of brands—Jack Link’s® , Lorissa’s Kitchen® , Golden Island® , BiFi® , and Peperami® and KOOEE!® to name a few—there’s nothing artificial about us. What you see is exactly what you get: humble, gritty, passionate people who show up every day ready to not just be a participant in the meat snack industry that the Link Family created, but to move faster, innovate harder and keep raising the bar so high, the rest of the world needs a ladder just to see it.

Dominating this space across the world takes a team. A team that runs together, succeeds together, and celebrates together. A team that’s full of relentless energy and spirit that can only be fueled by one thing: a fist full of our delicious meat snacks.

Real Meat Protein. Real People. Real Results. THAT is Link Snacks.

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/4

HANA 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.

• 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/4
  
  HANA 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 Dev Ops practices.
• Collaborate & Mentor: Partner with business, analytics, and IT teams; mentor junior engineers and promote best practices.

• Bachelor’s degree in Information Technology, Computer Science, or related field or equivalent experience.
• 7+ years professional experience as data engineer.
• Proven…