Senior Data Product Manager

PowerTalent: Recruitment, Selection, and Global Outsourcing

PowerTalent stands out for its customized talent solutions. As specialists in recruitment and selection, we streamline complex processes and find the best professionals worldwide.

We offer recruitment, outsourcing, and hybrid solutions, building local, nearshore, or offshore teams according to our clients’ needs.

With PowerTalent, we guarantee complete and efficient solutions, so our clients don’t have to worry about a thing.

We are looking for a Senior Data Product Manager to lead the transformation of how our organization creates value from data. Your mission will be to lead initiatives end-to-end, inspire a data-driven culture, and contribute to shaping a unified vision for our data products.

• More than 5 years of experience in the Data field as Product Manager or Product Owner with technical background.
• Expertise in Data Platforms and Architecture: In-depth knowledge of data architecture patterns, analytics engineering, and scalable data platforms.
• Data Modeling and Analysis: Proficient in dimensional modeling, advanced SQL, and applying different modeling techniques to suit business needs.
• Governance and Quality Standards: Experience in designing frameworks for governance, metadata, cataloging, and aligning product definitions.
• Cloud Knowledge: Familiarity with modern cloud platforms like Fabric, Azure, AWS, or GCP, including expertise in one or more cloud data warehouses.
• Product Management: Proven ability in managing product lifecycles from ideation to delivery, creating vision documents and strategies for data products or platforms.
• Complex Problem Solving: Capability to navigate uncertainty and solve complex problems at scale through discovery, design, and delivery phases.
• Analytical Tools: Proficiency in BI tools like Tableau, Looker, or Power BI.
• Cost and Compliance Awareness: Forward-thinking in cost-effective solutions, with a strong understanding of privacy and compliance in data.
• Technical Knowledge: Conceptual understanding of CI/CD pipelines, ML workflows, feature engineering, and defining SLAs, data contracts, and quality agreements.

• Contract or B2B, its up to you
• Hybrid Work
• Continuing education and professional development