Design, develop and maintain data solutions for data generation, collection, and processing, including building efficient data pipelines and implementing ETL processes.
Responsibilities
Design and develop data pipelines
Ensure data quality and integrity
Implement ETL processes
Collaborate with multiple teams
Lead development and optimization of data pipelines
Lead the design, implementation, and oversight of data governance and data quality frameworks for clients, ensuring trusted data assets and reliable data management practices.
Compensation
competitive compensation & benefits package
Responsibilities
Define and maintain business glossaries and metadata, including Critical Data Elements (CDEs)
Advise on data access and permissions, including RBAC and governance structures
Design and oversee data quality frameworks, validation rules, and metrics
Validate SQL queries and data quality implementations
Monitor and interpret data quality results across analytics environments
Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems.
Responsibilities
Expected to perform independently and become an SME.
Required active participation/contribution in team discussions.
Contribute in providing solutions to work related problems.
Collaborate with cross-functional teams to understand data requirements and deliver scalable data solutions.
Monitor and troubleshoot data pipelines to ensure reliability and performance.
Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL processes to migrate and deploy data across systems.
Transforms complex operational, production, and reliability data into actionable insights to improve decision‑making, optimize performance, and support strategic initiatives.
Responsibilities
Develop and maintain predictive, statistical, and reliability models using operational, production, and maintenance data to support performance optimization and risk reduction.
Analyze structured and unstructured data to identify trends, anomalies, and opportunities for operational improvement.
Perform forecasting, scenario modeling, and techno‑economic analysis to support planning, prioritization, and capital allocation decisions.
Design and support proactive monitoring tools (e.g., Operate‑by‑Exception workflows) to identify high‑risk assets and emerging operational issues.
Build and maintain dashboards, reports, and executive‑level summaries using business intelligence tools.
Requirements
Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, Analytics, or a related STEM field.
Nice to have: Master’s degree in Data Science, Statistics, Engineering, Analytics, or a related field
Nice to have: experience in oil and gas, industrial operations, manufacturing, or other asset‑intensive environments
Nice to have: familiarity with reliability modeling techniques (Weibull, Cox proportional hazards, Kaplan‑Meier)
Nice to have: experience with anomaly detection, predictive maintenance, and asset performance optimization
Vice President, Reinsurance Data, Analytics & Business Performance
Lead the strategy, roadmap, and delivery of data, reporting, analytics, and business performance capabilities across Everest's Reinsurance organization.
Compensation
The base salary range for this position is $201,000 - $245,000 annually. The offered rate of compensation will be based on individual education, experience, qualifications and work location.
Responsibilities
Develop and execute the Reinsurance data, analytics, reporting, and business performance strategy aligned with business objectives and enterprise data priorities.
Partner with senior leaders across Underwriting, Claims, Finance, Operations, and Executive Management to identify priorities and deliver data-driven solutions that improve business outcomes.
Own the Reinsurance data and analytics roadmap, translating business strategy into a prioritized portfolio of data, reporting, and analytics initiatives.
Collaborate with Technology and Enterprise Data & Analytics teams to define requirements, prioritize investments, and deliver scalable data and analytics capabilities.
Lead the development and continuous enhancement of operational, management, and executive reporting solutions, ensuring stakeholders have access to timely and actionable insights.
Requirements
Bachelor's degree in Business, Finance, Economics, Analytics, Information Systems, Mathematics, Data Science, or a related discipline
Lead the design, delivery, and operation of Domino’s enterprise data platforms and engineering capabilities, driving data strategy, architecture, and operational excellence.
Responsibilities
Define and evolve the enterprise data platform, engineering, and operations strategy
Develop and manage a multi-year roadmap aligned to business priorities and technology modernization goals
Drive a data-as-a-product culture focused on trusted, reusable, and business-aligned data assets
Serve as a trusted advisor to senior business and technology leaders on data platform investments and capabilities
Establish goals, operating metrics, and performance measures that drive continuous improvement and business value
Requirements
Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or related field