Overview Performs the analysis of business requirements and translates into an enterprise data design. Defines & develops architecture design standards, principles and best practices for end to end analytics development. Ensures analytics solutions are modelled following best practices and are performant and scalable. Works closely with Global Information Architecture to provide input into the standards, execute POC when needed and leverage Data & Analytics tools in alignment with Enterprise strategy Responsibilities Translates functional design into technical specifications and is able to supervise the team that develops code configuration Has a solid understanding of different components/tools required to deliver analytics products and identifies the architecture required for the different initiatives managed making sure it is affordable, scalable and aligned with Global Enterprise Architecture patterns and approved tools. Consult with cross-teams and prepare a project timeline. Develop strategic planning - should be able to provide the estimates for technical implementation. (Build, design and reporting) Lead and monitoring data modelling and design principles, standards and best practices Collaboarate and monitor the development of data model and design plan that maximizes re-usability and reduces redundancy. Makes sure the proposed data model is scalable and affordable. Oversee existing solutions/platform utilisation, impact, benefit and resolve day-to-day operational issues Helps to build and test solutions using the defined data model Work with the design team to create documentation for all the metadata related to data modelling and design Utilizes Agile and DevSecOps framework to maximize customer value and ensure fast time to market without compromising quality Act as the key liaison to all other functional areas, including business units, the information technology department, and outside vendors Work with IT team to build test scripts to enable UAT of tools and conduct UAT testing as required Conduct necessary QC checks across multiple data sources on a periodic basis to ensure ongoing data integrity and quality Consult broader team as needed to support them in accessing and using data to carry out their day-to-day tasks Qualifications Bachelor’s Degree in Engineering/Computer Science with 6+ years of related business experience Background in data and analytics, strong experience in data modelling - Microsoft Azure Data Lake & Databricks Should have experience as a Business Analyst for at least 2 years Should have experience in handling communications with Business and technical stakeholders Should have FMCG domain experience for at least 2 years Good understanding of data warehousing concepts and design principles. Any technology – Ideally Azure or any other databases Should have strong hands-on experience in writing SQL commands. Experience in understanding of data warehouses/data lakes build process Knowledge of ingesting data from multiple sources and working with cloud platforms (Preferably Azure) for data warehousing/advanced analytics. Proven experience in creating complex data models across multiple business needs and preparing data for reports/dashboarding consumption. Understanding and working knowledge of PySpark, ADLS concepts Exposure to “Point of Sale” (Nielsen, IRI, etc.) databases/metrics Experience in Business Intelligence tools like Tableau, Power BI Experience working with Agile methodology/ DevSecOps. Fluent in relational database concepts and dimensional modelling for decision support systems Experience managing technical teams, able to deliver high-quality products. Experience managing business interests, able to satisfy different stakeholders' expectations. Proven results in implementing solutions to support Analytics / Reporting requirements with a high degree of collaboration. Well versed in excel skills including but not limited to Data Manipulation and Analysis, Data Cleaning and Quality Assurance & Automation and Efficiency.