What are we looking for? 

• Bachelor’s degree in Analytics or related quantitative fields (Statistics, Operations Research, Mathematics, Econometrics etc.) Advanced degree is preferred.
• Minimum 3 years of experience in an Applied Data Engineering role or equivalent, ideally within the CPG, Consumer Products, Retail, Telecom, or Financial Services industries.
• Technical expertise in Big Data Tech Stack and experience in database and Data Engineering capabilities
• Rich heritage in designing and building databases, analytics, and BI platforms with Big Data.
• Experience with cloud-based computing platforms like AWS or Azure, Databricks, technologies across traditional and contemporary software (e.g. SQL Server, Hadoop, NoSQL DB), programming languages such as SQL, Java, C#, C++, Python, R, and visualization tools
• Experience with DevOps principles such as CI/CD, unit testing, and AGILE development.
• Strong problem solving, communication, presentation, and stakeholder engagement skills.
• Planning, project management, and organizational orchestration skills and a strong attention to detail

What will be your key responsibilities? 

• Your deep expertise in data analytics, as well as strong practical experience with modern engineering technologies will enable you and the team to intelligently transform data into value, innovate, create high-standard robust production capabilities and deliver increased business benefits.
• You will manage engineering projects in collaboration with other team members (including with offshore talent partners) to ensure rapid development of quality, scalable and sustainable data solutions, with global best practices and consistency. 
• You will manage the design of our cloud-based data solutions and models to enable insights and ensure the right technologies are in place for our needs – deliver engagements with the most up-to-date capabilities available in the industry.
• Engage and collaborate with data and IT owners across Mars to drive data quality and availability, and ensure data improvement plans in place and support effective governance, harvest, and maintain coherent Data Models to ensure holistic leadership of the data solution within the environment.
• Day-to-day you will work in multidisciplinary teams & collaborate with Mars Global Analytics, Big Data Engineering, and Advanced ML teams.

• Engage with different teams to understand the business vision and opportunities, build solutions using existing or new data sets to create scalable, robust, modularised solutions.
• Contribute to Architecture Review process by assessing, authorizing solutions proposed by different projects, ensuring that standards and patterns are followed by all projects under Supply Chain Analytics area.