Manager, Data Engineering

Casey's; Ankeny (IA); On-site; USD 125,100 - 174,100; Full time

Benefits offered by this job

401k matching

Paid time off

Onsite cafeteria

Volunteer time

Onsite Child Development Center

Job summary

Casey’s is seeking a Manager, Data Engineering to drive the strategy, delivery, and reliability of enterprise data products across the organization. You will lead a team of data engineers delivering data products for analytics, AI, and business insights.

This role requires strong technical leadership, collaboration with product and business partners, and a passion for turning data into business value. The position focuses on enterprise datasets including Guest, Store, and Product data assets.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Data Analytics, Engineering, Mathematics, or related field, or equivalent work experience.
• Seven (7)+ years of progressive experience developing and delivering enterprise data, analytics, or engineering solutions.
• Three (3)+ years of experience leading and developing technical teams.
• Experience managing teams responsible for data engineering, analytics engineering, business intelligence, or enterprise data platforms.
• Strong understanding of data architecture, data modeling, data integration, and modern data engineering practices.
• Experience building and supporting cloud-based data platforms and enterprise-scale data solutions.
• Strong leadership, communication, organizational, analytical, and problem-solving skills.
• Familiarity with data observability, metadata management, and data catalog solutions.

Responsibilities

• Lead a high-performing team of Data Engineers responsible for building, maintaining, and supporting enterprise data products and datasets.
• Define priorities with stakeholders and deliver high-value data solutions aligned to business outcomes.
• Partner with Product to co-own the data product roadmap and ensure delivery as a unified team.
• Drive the design and implementation of scalable data pipelines, data models, and reusable data products.
• Promote data engineering best practices for data quality, performance, security, and governance.
• Leverage AI-assisted engineering practices to accelerate delivery and improve quality.
• Ensure data products are reliable, well-documented, and monitored.
• Lead efforts to optimize data platform performance, scalability, and cost efficiency.
• Set team goals and roadmaps aligned with organizational priorities.
• Champion data product thinking with defined ownership and SLAs.

Skills

Data architecture

Data modeling

Data integration

Leadership

Communication

Analytics

Education

Bachelor's degree in CS/IT/Analytics/Engineering

Tools

Databricks

Azure Data Lake Storage

Azure Data Factory

Microsoft Fabric

Snowflake

Power BI

Tableau

Looker

Spark

SQL

Python

Job description

Join Casey's Data & Analytics team as the Manager, Data Engineering! This role leads the Marketplace Data Engineering team delivering the data products that enable insights, analytics, data science, and AI across Casey's. Working closely with business and technology partners, you will lead a team of data engineers focused on building scalable, reliable, and reusable data solutions that drive business outcomes.

As the Manager, Data Engineering, you'll be responsible for the strategy, delivery, and operational excellence of enterprise datasets and data products. Success in this role requires strong technical and people leadership, deep partnership with product and business stakeholders, and a passion for turning data into business value.

Key Responsibilities

• Lead a high-performing team of Data Engineers responsible for building, maintaining, and supporting enterprise data products and datasets that enable business intelligence, analytics, data science, and AI initiatives. Responsible for hiring, coaching, performance management, career development, and succession planning of direct reports.
• Create strong partnerships with business stakeholders, Product Owners, Data Scientists, and Analysts to define priorities and deliver high-value data solutions aligned to business outcomes. Partner closely with Product to co-own the data product roadmap, ensuring Engineering and Product operate as a unified, outcome focused delivery team.
• Drive the design and implementation of scalable data pipelines, data models, and reusable data products.
• Establish and promote data engineering best practices related to data quality, performance, security, and operational excellence.
• Leverage AI-assisted engineering practices and emerging technologies to accelerate delivery, improve solution quality, and enhance team productivity.
• Ensure data products are reliable, trusted, and well-documented through appropriate testing, monitoring, governance, and support processes.
• Lead efforts to optimize data platform performance, scalability, reliability, and cost efficiency.
• Define team goals and roadmaps that align with organizational priorities while ensuring work is appropriately prioritized across business and technology stakeholders.
• Champion data product thinking by treating datasets as strategic assets with defined ownership and service levels.
• Own the strategy, governance, reliability, and evolution of enterprise data products including customer, store, and operational 360 datasets (Guest, Store, Product) that serve as foundational assets for technology, analytics, AI, and business teams.

Compensation: Starting pay range: $125,100 - $174,100. 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 an annual cash bonus based on company performance and an annual equity grant in the form of Restricted Stock Units (RSUs). Our full salary range for this role does extend beyond the hiring range listed, allowing team members the opportunity to continue to grow within the company.

What you can expect when you join the Casey's Team:

• A transformative culture putting service first and taking pride in caring for our guests, our communities, and each other.
• Opportunities to use cutting edge technologies and enterprise-wide collaboration to enable our strategy and drive world class service.
• We're here for families! Great benefits including choices in medical plans, dental, vision, life insurance, charitable giving programs, parental leave and an onsite Child Development Center.
• Competitive pay, 401k company match up to 6%, vacation & sick time, paid holidays, volunteer time, and an onsite cafeteria.
• Dress for your day dress code, jeans are welcomed!
• The opportunity to work for a big company that has not lost our small company feel. Our senior leadership team is engaged, involved and accessible!

What are you waiting for? Come be a part of a company that is growing, transforming and is here for good!

Requirements

• Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, Mathematics, or related field, or equivalent work experience.
• Seven (7)+ years of progressive experience developing and delivering enterprise data, analytics, or engineering solutions.
• Three (3)+ years of experience leading and developing technical teams.
• Experience managing teams responsible for data engineering, analytics engineering, business intelligence, or enterprise data platforms.
• Strong understanding of data architecture, data modeling, data integration, and modern data engineering practices.
• Experience building and supporting cloud-based data platforms and enterprise-scale data solutions.
• Strong leadership, communication, organizational, analytical, and problem-solving skills.
• Demonstrated ability to translate business requirements into scalable technical solutions and drive execution through delivery.
• Preferred Skills:
• Experience with modern cloud data platforms such as Databricks, Azure Data Lake Storage, Azure Data Factory, Microsoft Fabric, Snowflake, or similar technologies.
• Experience developing and optimizing large-scale ETL/ELT data pipelines using SQL, Python, Spark, or similar technologies.
• Knowledge of business intelligence platforms such as Power BI, Tableau, or Looker.
• Experience supporting machine learning, AI, and advanced analytics initiatives through curated and governed data assets.
• Familiarity with data observability, metadata management, and data catalog solutions.