Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce
If you are passionate to work on unstructured business problems that can be solved using data, we would like to talk to you.
We are looking for a Data Steward to deliver insights on a daily basis. The ideal candidate will have Enterprise data governance expertise and will Serve as the primary liaison between the global data governance team and businesses to ensure alignment with Enterprise Data Governance (EDG) processes, rules, and standards
Requirements
1. 5-10+ years of experience working in Data Governance or Data Management experience within global CPG (Consumer Packaged Good) company, Supply Chain or similar industry.
2. Strong data management background who understands data, how to ingest data, proper data use/consumption, data quality, and stewardship.
3. Experience in Azure Data Steward, Data management frameworks - DAMA - DMBOK, Data regulation and data governance (Alterxy, Informatica),
4. Data Visualization tools - Talbeau and Power BI - Experience working in Agile environments, participating in sprints, and collaborating with cross- functional teams
5. Ability to partner with both business and technical subject matter experts to ensure standardization of operational information and execution of enterprise-wide data governance policies and procedures are defined and implemented.
6. Preferred experience with Informatica (EDC, Axon, IDQ), Intermediate – Advanced Excel
Responsibilities
7. Support strategic initiatives that depend on the consumption of Supply Chain & Product data
8. Develop and implement data governance policies and standards
9. Ensure compliance with data regulations and internal policies
10. Facilitate data stewardship meetings and maintain documentation
11. Monitor data quality metrics and perform data quality assessments
12. Identity and resolve data quality issues
13. Implement data cleansing processes and procedures.
14. Manage the data lifecycle from creation to archival or deletion
15. Collaborate with cross-functional teams to understand data needs and usage
16. Provide insights on data trends and usage through regular reporting
17. Support data-driven decision-making processes across the organization
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.