SUMMARY Responsible for independently designing, building, and operating complex divisional data software and pipelines. Converts ambiguous business needs into scalable technical solutions, leads delivery of significant data product components, and raises engineering quality through sound architecture, testing, observability, and governance. Mentors less experienced engineers and coordinates effectively across technology and business teams. ESSENTIAL DUTIES AND RESPONSIBILITIES Leads technical discovery and translates complex divisional requirements into data architecture, interfaces, and delivery plans. Designs, builds, and operates scalable, secure, and resilient data ingestion, ELT, and integration services. Develops reusable frameworks, libraries, and patterns that improve engineering consistency and delivery speed. Designs dimensional and other fit-for-purpose data models; optimizes storage, query performance, and compute utilization. Establishes appropriate automated testing, data quality controls, monitoring, alerting, and recovery practices. Leads investigation of complex data defects and production incidents; drives root cause analysis and durable remediation. Ensures solutions meet divisional and enterprise requirements for privacy, security, governance, lineage, and retention. Facilitates technical reviews and makes recommendations on tools, design tradeoffs, and implementation approaches. Partners with product, analytics, architecture, and business stakeholders to prioritize work and manage dependencies. Mentors engineers through pairing, design feedback, code review, and sharing of engineering practices. Communicates delivery status, technical risks, operational health, and data limitations to appropriate stakeholders. Performs all duties in accordance with all company policies and procedures, and all federal, state and local laws, wherein the Company operates. Performs other duties as assigned. QUALIFICATIONS EDUCATION/EXPERIENCE Bachelor's Degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related field; or an equivalent combination of education and experience. Five (5) or more years in data engineering, software engineering, data integration, or related work. One (1) or more years of Insurance industry experience.

SKILLS

Knowledge of data architecture, data modeling, distributed processing, and pipeline orchestration Knowledge of cloud data platforms, APIs, and scalable integration patterns Skills in SQL and Python or another production programming language Skills in data architecture, modeling, distributed processing, and pipeline orchestration Skills in using cloud data platforms, APIs, and scalable integration patterns Skills in testing, observability, performance tuning, and production incident response Skills in technical communication, stakeholder partnership, and mentoring Ability to balance reliability, security, maintainability, delivery time, and cost

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