Key Roles and Responsibilities 1. Data Acquisition, Cleaning & Storage Design, develop, and maintain robust data pipelines (ETL/ELT) from multiple data sources. Implement data cleaning, standardisation, deduplication, and enrichment processes. Establish and monitor data quality frameworks (completeness, accuracy, timeliness). Ensure secure data storage and enforce access controls in line with governance standards. 2. Data Warehouse & Data Modelling Design and implement scalable Data Warehouse and/or lakehouse architectures. Develop dimensional data models (fact and dimension tables) and curated data marts. Maintain comprehensive documentation including data dictionaries, lineage, and pipeline runbooks. Optimise data performance and cost efficiency (e.g., indexing, partitioning, query tuning). 3. Pricing Strategy Automation Build and maintain pricing analytics frameworks, including pricing structures, discount models, and margin analysis. Develop automated pricing recommendations using rule-based and statistical methods (e.g., regression, clustering). Implement workflows for approvals, audit trails, and exception handling. Monitor and refine pricing performance using key metrics such as margin, revenue, and win rates. 4. Analytics, Reporting & Decision Support Develop dashboards and reports for business stakeholders (e.g., margin performance, utilisation, pipeline tracking). Translate business requirements into analytical solutions and actionable insights. Enable self-service analytics through well-defined semantic layers and standardised KPIs. 5. Stakeholder Collaboration & Data Governance Work closely with cross‑functional teams to define data requirements and KPIs. Establish and enforce data governance practices, including naming conventions and access controls. Support analytics roadmap planning and continuous improvement initiatives. Education and Experience Minimum Requirements Bachelor’s degree in Data Science, Computer Science, Statistics, Information Systems, or a related field. 4–7+ years of experience in data analytics, data engineering, or a related role. Proven experience in building and maintaining data pipelines and data warehouse solutions. Demonstrated experience in pricing, commercial analytics, or revenue optimisation. Advantageous Postgraduate qualification in a relevant field. Experience with experimentation (A/B testing), forecasting, or optimisation techniques. Exposure to CRM/ERP systems and master data management (MDM). Experience with data observability tools and service-level agreements (SLAs). Skills and Knowledge Technical Skills Strong proficiency in SQL and data modelling techniques. Experience with ETL/ELT tools and modern data platforms (e.g., cloud data warehouses). Proficiency in data visualisation tools (e.g., Power BI, Tableau, or similar). Familiarity with programming languages such as Python or R for analytics. Knowledge of statistical modelling techniques (regression, clustering, forecasting). Analytical & Business Skills Strong analytical thinking and problem-solving ability. Ability to translate complex data into clear business insights. Understanding of pricing strategies, margin optimisation, and commercial dynamics. Soft Skills Strong communication and stakeholder management skills. Ability to work cross‑functionally in a fast‑paced environment. High attention to detail and commitment to data quality and governance. Self‑driven with the ability to take ownership and deliver end‑to‑end solutions. #J-18808-Ljbffr