Principal Data Engineer – CPS DataValidation Platform (OmniShopper & Homescan)

Platform Ownership & Production Leadership Own the overall health, reliability, performance, and scalability of the DataValidation platform. Serve as the primary engineering escalation point for production incidents and business-critical issues. Lead incident management, root cause analysis, and post-incident remediation activities. Drive improvements in observability, monitoring, alerting, and operational excellence. Establish and maintain operational KPIs, SLAs, and platform health metrics. Technical Leadership Define and execute the technical strategy and roadmap for the DataValidation platform. Participate to architecture decisions across both on-premise and Azure-based systems. Ensure solutions are scalable, maintainable, secure, and cost-effective. Review system designs and provide technical guidance to development teams. Balance technical debt reduction with business delivery commitments. Act as the engineering lead for strategic OmniShopper initiatives. Collaborate with Product Leadership and PMO to define technical solutions supporting business objectives. Coordinate execution across multiple engineering and business teams. Ensure DataValidation capabilities align with future OmniShopper and Homescan requirements. Cross-Functional Collaboration Partner closely with: Data Science teams PMO Operations teams Product Leadership Global Engineering teams Responsibilities include: Translating business requirements into technical solutions. Managing technical risks and dependencies. Driving prioritization discussions. Communicating platform health and roadmap updates to stakeholders. Influencing decision-making without direct authority. Experience 10+ years of software engineering experience. 5+ years in Staff Engineer, Principal Engineer, Architect, or equivalent technical leadership roles. Experience owning mission-critical production systems. Experience supporting enterprise-scale data platforms. Proven success influencing multiple organizations and stakeholders. Technical Skills Strong hands-on experience with: Python Oracle Database Linux environments SQL performance tuning Azure Data Services PySpark Parquet datasets ETL and data engineering frameworks Data quality and validation platforms Leadership Skills Strong stakeholder management skills. Excellent communication with technical and non-technical audiences. Ability to work effectively across global teams. Strong ownership mindset and bias for action. Experience leading complex incident resolution efforts. Preferred Qualifications Retail measurement, consumer panel, or syndicated data domain experience. Experience working with OmniShopper, Homescan, or similar consumer analytics platforms. Experience working with Data Science and advanced analytics teams. Knowledge of modern data quality, governance, and observability frameworks. 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