Senior Analytics Engineer

POSITION SUMMARY Design, develop, and govern curated enterprise datasets that support analytics, machine learning, and digital product capabilities. This role leads the development of Gold-layer datasets within the enterprise data platform and ensures that business metrics, dimensional models, and curated data assets are structured consistently and reliably. The position plays a working leadership role by guiding data engineers in modeling practices, accelerating delivery of early-value datasets, and establishing standards that improve trust in enterprise data. Operating within a cross-functional environment, this role collaborates closely with Data Engineering, Data & Analytics, Digital Product teams, and IT to ensure business-ready datasets are scalable, well-documented, and aligned with operational and strategic objectives. AREAS OF RESPONSIBILITY Data Modelling and Curation Design and develop curated datasets that support enterprise reporting, analytics, and digital platform requirements. Establish dimensional models, fact tables, and standardized data structures aligned with business definitions. Ensure consistency of metrics, KPIs, and business logic across datasets. Validate accuracy and usability of curated datasets prior to production release. Maintain reusable modeling patterns and standardized transformation logic. Data Modelling Leadership and Standards Development Establish modeling standards including naming conventions, schema design, and documentation practices. Provide technical leadership in dimensional modeling and semantic structure development. Review and approve modeling designs created by data engineers. Ensure business definitions are consistently implemented across datasets. Promote modeling best practices that improve scalability and maintainability. Delivery and Data Value Acceleration Identify and prioritize high-value datasets that deliver immediate business impact. Lead delivery of foundational datasets that support early analytics and reporting needs. Work with stakeholders to define and deliver quick-win data solutions. Support rapid deployment of datasets required for operational and decision-making use cases. Collaboration with Data Engineering and Analytics Teams Collaborate with Data Engineers to ensure smooth transformation from Silver to Gold layers. Work closely with Data & Analytics teams to translate analytical requirements into structured datasets. Support Digital Product teams with curated datasets required for platform functionality. Participate in cross-functional planning and delivery initiatives. Technical Mentorship and Capability Development Provide guidance to data engineers on modelling practices and transformation logic. Review data models and provide technical feedback to improve quality. Support skill development and knowledge sharing within the team. Promote engineering discipline and continuous improvement practices. People Management Performance Management: Manage and drive high performance among direct reports, and help them achieve their performance goals . This also includes conducting performance evaluations. Coaching and Mentoring: Provides guidance to direct reports in performing their areas of responsibility, and supports their growth and development. Employee Engagement: Implement initiatives and provide a work environment that will promote employee engagement and high commitment to the company. QUALIFICATIONS Education Bachelor’s Degree in Computer Science, Information Systems, Data Engineering, Mathematics, or a related discipline. Relevant Experience Minimum 5 years of experience in analytics engineering, data engineering, or data modelling roles. Strong hands-on experience designing dimensional models and curated datasets. Proven experience working with modern data warehouse platforms (e.g., Snowflake or equivalent). Experience translating business logic into structured data models. Experience mentoring junior engineers or providing technical leadership. Licenses / Certifications Relevant certifications in data engineering or analytics platforms are an advantage. Business Understanding Strong understanding of business reporting and analytics workflows. Familiarity with KPI development and business metric alignment. Ability to translate business requirements into technical data structures. Owns final approval of curated dataset definitions prior to production release.