Please review the job profile below and apply today!
Position will follow our hybrid schedule: Monday-Wednesday in Grand Rapids MI Corporate office, Thursday-Friday remote.
What You'll be Doing:Data Engineering, Analytics & AI/Automation- Lead the design, development, and implementation of data engineering, analytics, and AI/automation solutions to support business objectives.
- Oversee data architecture, ensuring data integrity, security, and scalability.
- Manage and mentor a team of data engineers, data scientists, and analysts, fostering a culture of collaboration and continuous improvement.
- Collaborate with cross-functional teams to identify data needs and develop strategies to leverage data for business insights and decision-making.
- Drive adoption of best practices in data management, analytics, and AI/automation.
- Ensure compliance with data governance policies and regulations.
- Stay current with industry trends and emerging technologies in data engineering, analytics, and AI/automation.
- Develop and manage budgets, resources, and timelines for data projects.
- Ensure all teams follow engineering and IT standards for change controls and IT practices for production systems.
Enterprise Quality Adoption - Own the enterprise quality strategy - embed quality into the software development lifecycle, not onto it.
- Drive adoption of test automation, shift-left testing, and continuous quality practices across all engineering teams.
- Define and enforce quality standards, frameworks, and tooling across the portfolio; ensure consistent adoption at scale.
- Partner with engineering and product teams to establish quality gates that protect production stability without slowing delivery.
- Report on quality health across domains, with clear visibility into defect rates, test coverage, and release readiness.
Engineering Delivery Performance - DORA Metrics - Establish DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, Mean Time to Recovery) as the standard measurement framework for engineering delivery health.
- Own the baseline, targets, and reporting cadence for DORA metrics across teams; surface trends to senior leadership with clear business context.
- Use DORA data to identify delivery bottlenecks, prioritize platform and process investments, and demonstrate improvement over time.
- Connect engineering performance to business outcomes - faster delivery and lower failure rates translate directly to customer experience and cost efficiency at Meijer's scale.
- Partner with DevOps and platform teams to build the tooling and observability infrastructure required to measure and improve DORA outcomes.
IT General Controls (ITGC) - Accountable for ITGC compliance across the technology domains in scope - change management, access controls, computer operations, and program development controls.
- Partner with Internal Audit, Compliance, and Finance to ensure controls are designed, operating effectively, and audit-ready.
- Own remediation of ITGC deficiencies; drive root cause analysis and sustainable control improvements rather than point-in-time fixes.
- Ensure all teams understand and operate within ITGC requirements as a standard part of the delivery process - not a compliance afterthought.
- Maintain documentation, evidence, and control narratives sufficient to support SOX and internal audit cycles.
What You Bring with You (Qualifications):Education - Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. Master's degree preferred.
Experience - 10+ years of experience in data engineering, analytics, and AI/automation, with at least 5 years in a leadership role.
- Proven experience establishing and scaling enterprise quality practices across large engineering organizations.
- Hands-on experience implementing DORA metrics programs and using delivery performance data to drive engineering improvement.
- Demonstrated experience with ITGC compliance, SOX controls, or equivalent control frameworks in an enterprise environment.
- Track record of managing multiple complex programs simultaneously in a fast-paced, high-scale environment.
Technical Skills - Strong knowledge of data architecture, data warehousing, ETL processes, and data modeling.
- Proficiency in Python, Java, or Scala; experience with big data technologies including Spark, Kafka, and Databricks.
- Expertise in machine learning and AI frameworks (TensorFlow, PyTorch, scikit-learn or equivalent).
- Familiarity with CI/CD tooling, test automation frameworks, and observability platforms used to track delivery and quality metrics.
- Working knowledge of ITGC control domains: logical access, change management, computer operations, and program development.
Leadership & Communication - Strong communication and interpersonal skills; able to collaborate with and influence stakeholders at all levels.
- Speaks the language of business outcomes - connects technology performance to cost, revenue, and customer experience.
- Proven ability to manage multiple priorities and drive accountability across matrixed teams.
