Senior Data Engineer

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, where you will work closely with other members of the Data Engineering, Analytics, and Technology teams to solve challenging data problems with cloud technology.

The primary technologies utilized in this role include: Databricks (Python, PySpark, SQL), Azure Data Factory, and Anomalo.

Key Responsibilities

• Leads complex data engineering initiatives, actively participating in requirements gathering and continuously refining technical solutions as business needs evolve.
• Mentors other engineers on software/data engineering best practices, data modeling, and pipeline development.
• Performs thorough testing of data pipelines and data models to ensure data is accurate and pipelines are resilient and self-healing.
• Evaluates source data systems and understands how to extract and model data for analytics and operational use cases.
• Ingests data from API, streaming, event, and batch source systems.
• Evaluates the technology landscape and makes recommendations for continuous improvement of the data platform.
• Builds, maintains, and troubleshoots CI/CD pipelines in GitHub.
• Acts as the primary point of escalation for the Data Engineering team to troubleshoot data and platform issues.
• Provides support for the data platform as part of an on-call rotation.

Casey's is not able to offer employment sponsorship for work authorization in the United States for this role now or in the future.

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.

Requirements

• 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
• Prior experience in Software Engineering is a plus

Compensation

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 does extend beyond the typical hiring range listed, allowing team members the opportunity to continue to grow within the company.