Hiring: Data Reliability Engineer Company: Little Caesars Pizza Location: Detroit, MI Job Posted Time: 2026-09-10 12:58:27 Employment Type: Remote Target Skills & Keywords : Azure, Azure DevOps, CI/CD, Databricks, ELT, ETL, Git, Machine Learning, Python, Quality Assurance, Regulatory Compliance, SQL, Snowflake About the job Required Skills: •Serve as the technical owner of the enterprise Data & Model Quality Framework, establishing standards for monitoring, validation, reliability, SLAs/SLOs, and alerting for critical data products. •Partner with technical and business teams to proactively identify issues, conduct root-cause analysis, and continuously improve the accuracy and reliability of enterprise reporting, analytics, machine learning models, and AI-enabled solutions. •Own the operational health and observability of enterprise data platforms by developing automated monitoring, alerting, and performance capabilities across pipelines, reporting, data and machine learning models, and platform services. •Proactively identify anomalies, reduce operational risk, and improve reliability across the Data & Analytics ecosystem. •Advance the organization's data foundations strategy through the implementation of technical governance capabilities that improve transparency, discoverability, and trust in enterprise data. •Establish and maintain metadata management, data lineage, catalog management, and asset governance practices that support data quality, business understanding, regulatory compliance, and AI readiness. •Release Management & Quality Assurance •Design and maintain testing, validation, and deployment processes that ensure enterprise data products are released with confidence. Qualifications: •Technical Problem Solving: The role requires investigating complex data issues across multiple systems, platforms, and technologies. Success depends on identifying root causes, evaluating alternatives, and implementing durable solutions that improve reliability and reduce operational risk. •Dealing with Ambiguity: The role requires balancing competing priorities while making technical decisions in environments where information may be incomplete, evolving, or ambiguous. Decisions should consider scalability, maintainability, operational impact, and business value. •Collaboration & Communication: Success depends on working effectively across Data Governance, Data Engineering, Analytics Engineering, Data Architecture, Business Intelligence, IT, and business stakeholders. The role regularly communicates technical concepts to audiences with varying levels of technical expertise. •Platform & Operational Excellence: The role emphasizes disciplined engineering and operational practices, including monitoring, testing, automation, release management, observability, documentation, and continuous improvement. •Continuous Learning & Innovation: The role requires staying current with evolving technologies, data management practices, AI capabilities, and engineering approaches. Success includes applying this knowledge to improve enterprise data reliability, operational efficiency, and business outcomes. •Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, Mathematics, or a related field. A minimum of four (4) years of relevant industry experience may be considered in lieu of a degree. •Data engineering, ETL/ELT development, and data integration processes •Cloud-based data platforms such as Databricks, Azure, Snowflake, or equivalent technologies •Data quality monitoring, testing, validation, and observability frameworks •Data modeling, semantic models, reporting platforms, and business intelligence solutions Compensation: •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!