- Collaborate with engineering and data architecture teams to implement automated data validation, anomaly detection, and reconciliation processes that minimize downstream data errors.

- Translate complex business requirements into detailed technical specifications and user stories to guide development cycles and ensure high-quality delivery.

- Manage the product lifecycle using agile methodologies, facilitating sprint planning and backlog grooming to maintain a consistent velocity of feature releases.

- Partner with stakeholders across business units to identify critical data pain points and implement solutions that enhance data trust and regulatory compliance.

- Monitor key performance indicators related to data health and product usage, leveraging insights to iterate on features and improve the overall user experience.

Required Skillset :

- Demonstrated expertise in managing data quality products or platforms, with a deep understanding of data profiling, lineage, and metadata management.

- Proven ability to navigate cloud-native environments, including GCP, AWS, or Azure, to architect and deploy scalable data solutions.

- Exceptional proficiency in agile project management tools such as JIRA and Confluence to manage documentation, track progress, and foster team collaboration.

- Strong analytical mindset with the ability to communicate complex technical concepts to non-technical stakeholders, ensuring alignment across diverse teams.

- Excellent interpersonal skills, with a track record of influencing cross-functional partners and driving consensus in a fast-paced, matrixed environment.