Senior Data Engineer

Senior Data Engineer at Casey's

At Casey's, every event generates data: a pizza delivery, filling up a gas tank, a truck pulling into the lot, pouring a cup of coffee. Our mission is to use that data to generate insights and help solve the organization’s biggest challenges. Our team partners with departments across Casey’s to make sense of data and provide direction to decision makers. To enable our strategy, we utilize cutting‑edge technology tools for data collection, transformation, and analysis.

Are you driven to wrangle, cleanse, and transform data? Do you want to partner with leaders to make data‑driven decisions? Does diving into a wide variety of data to extract insights excite you? We’re looking for innovators who can take an idea from the whiteboard to the boardroom. If that’s you, let’s talk.

The Senior Data Engineer will be responsible for developing data ingestion and transformation frameworks, data modeling for analytics, developing data pipelines, CI/CD, data platform performance/cost optimization, and helping enhance our data platform architecture. This is a collaborative role; you will work closely with other members of the Data Engineering, Analytics, and Technology teams to solve challenging data problems with cloud technology.

• Lead complex data engineering initiatives, actively participating in requirements gathering and continuously refining technical solutions as business needs evolve.
• Mentor other engineers on software/data engineering best practices, data modeling, and pipeline development.
• Perform thorough testing of data pipelines and data models to ensure data is accurate and pipelines are resilient and self‑healing.
• Evaluate source data systems and understand how to extract and model data for analytics and operational use cases.
• Ingest data from API, streaming, event, and batch source systems.
• Evaluate the technology landscape and make recommendations for continuous improvement of the data platform.
• Build, maintain, and troubleshoot CI/CD pipelines in Git Hub.
• Act as the primary point of escalation for the Data Engineering team to troubleshoot data and platform issues.
• Provide support for the data platform as part of an on‑call rotation.

This position requires authorization to work in the U.S. without the need for employment‑based immigration sponsorship now or in the future. Casey’s will not provide sponsorship or employer support for applications or petitions for H‑1B, L‑1, TN, O‑1, E‑3, H‑1B1, F‑1 CPT, F‑1 OPT, J‑1, or any other employment‑based visa.

This role does not allow for 100% remote work. Qualified out‑of‑state candidates must be willing to relocate and will need to live within a daily commutable distance of Casey’s Store Support Center in Ankeny, IA and be willing to work onsite 5 days a week.

Starting pay range: $101,700 - $139,800. Actual pay may vary based on Casey’s assessment of the candidate’s knowledge, skills, abilities (KSAs), related experience, education, and qualifications. Other factors impacting pay include local prevailing wages and internal equity. This position is eligible for annual cash bonuses based on company performance. Our full salary range for this role extends beyond the typical hiring range listed, allowing team members the opportunity to continue to grow within the company.

• Bachelor’s degree in Computer Science, Data Analytics, Engineering, Information Technology, or equivalent years of related work experience.
• At least five (5) years of experience designing and developing enterprise data solutions and integrations, ETL, data warehousing, data modeling (star schema, etc.).
• Strong proficiency in Python, PySpark and SQL.
• Experience with Databricks, Snowflake, or other modern data platform.
• Comfort with a variety of data sources including APIs, streams, events, databases, files, etc.
• Hands‑on experience with Azure, including ADLS Gen2, Data Factory, Key Vault, and Function Apps (or other equivalent cloud technology).
• Experience implementing CI/CD and automated testing for a data team.
• Familiarity with data governance concepts: data cataloging, tagging, handling sensitive data.

Mid‑Senior level

Full‑time

Information Technology

Food and Beverage Services