We are seeking a Technical Product Manager that will play a key role in the evolution of a modern data platform and data product ecosystem, working closely with Data Engineering, Analytics, and Data Science teams to build scalable data capabilities on Databricks and deliver data-driven solutions that create business value.
Responsibilities
- Define, prioritize, and deliver data products that support business objectives and drive measurable value.
- Collaborate closely with Data Engineering teams to support the development and evolution of a Databricks-based data lake and associated data platforms.
- Translate business needs into clear product requirements, user stories, and delivery roadmaps.
- Partner with analytics, data science, and business stakeholders to identify opportunities for new data-driven products and capabilities.
- Drive product decisions using data, customer feedback, and business priorities.
- Ensure data products are scalable, reliable, and aligned with enterprise data strategy.
- Work across cross-functional teams to remove blockers, solve complex challenges, and deliver outcomes.
- Define success metrics and monitor product performance after launch.
- Promote best practices in data governance, data quality, and product lifecycle management.
- 10+ years of experience in Product Management, Data Product Management, Analytics Product Management, or related fields.
- Strong understanding of modern data platforms, data architecture, and data lifecycle concepts.
- Experience working with Databricks or similar cloud-based data platforms.
- Proven ability to translate complex technical concepts into business value.
- Experience partnering with Data Engineering, Analytics, and Data Science teams.
- Strong problem-solving skills with a practical, solution-oriented mindset.
- Experience in leading cross-functional, highly analytical, and technical teams and enterprise-wide programs, operating and influencing effectively across the organization and within complex contexts.
- Experience with advanced analytic techniques, such as factor analysis, predictive modelling, logistic regression, cluster analysis, segmentation, attitudinal/motivational analysis, concept/copy testing, sales forecasting, response prediction, advertising effectiveness, consumer profiling, marketing mix and ROI measurement.
Nice to have Qualifications
- Experience within Consumer Packaged Goods (CPG) environments.
- Familiarity with retail, consumer, marketing, sales, or measurement-related data concepts.
- Exposure to machine learning, predictive analytics, or data science workflows.
- Experience working in cloud-based data ecosystems (AWS, Azure, or GCP).
Our benefits:
📚 Learning Opportunities:
- Certifications in AWS (we are AWS Partners)