Sr. Data Steward Consultant

Sr. Data Steward Consultant

• Bachelor or Master degree (MBA included). Preference computer science, statistics, data science, business • Minimum 7 years of working experience, in a fast-paced environment, preferably in CPG environment, previous experience in working on with operations and sustainability data sets is valued. • Strong understanding of code languages for data manipulation. SQL required, Snowflake and Python experience are helpful. • Solid understanding on BI tools and recent work done on manipulating data for BI solutions, preferably tableau. • Strong project management skills required, understand what to prioritize and follow through. • Strong social skills, with the ability to understand the context and applying it to drive the analytics agenda. • Strong social skills, with the ability to understand the context and applying it to drive the analytics agenda. • Familiarity and knowledge of Company Operations and metrics (understand CFR, on time %, forecast bias and other performance metrics) • Familiarity with systems like Snowflake, Tableau, Power BI is recommended • Strong ownership, committed to drive positive change even in challenging environments • As Global Data Steward, maintain a conceptual structure of data and formulas used, design and recommend appropriate analytical approaches to improve business reporting and assure data quality. • Be an agent of change into Kraft Heinz Company organization, using data, statistics, process and social skills to move different partners towards the goal of optimization of usage of new development data • Chief a positive environment into your team, genuinely interested in the well-being and happiness of your colleagues • Partner with Kraft Heinz' Global and local logistics teams and other teams on structuring large scale data sets and data projects. • Collaborate closely with vendors, application owners, and KHC teams from different business areas in each country to drive insights and deliver projects globally • Liaison with internal and external partners to understand their business peculiarities and develop and implement data sets that will support analytics on their business. • Maintain a backlog of desired improvements and bugs. Guide team members in solving the backlog issues and develop improvements.