Senior Data Product Manager - Job Description

Introduction

Join an amazing company where you can work with cutting-edge technologies and platforms. Give your career an Infinite edge, with a stimulating environment and a global work culture. Be a part of an organization where we celebrate integrity, innovation, collaboration, teamwork, and passion. A culture where every employee is a leader delivering ideas that make a difference to this world we live in.

In the Senior Data Product Manager responsibilities include, although not limited to:

- Define and own the data product vision, strategy, and roadmap aligned with business priorities and data-driven outcomes.

- Translate business needs into clear product requirements, user stories, acceptance criteria, and prioritized backlogs.

- Lead the full lifecycle of data products from discovery and design to delivery, adoption, and continuous improvement.

- Partner closely with Databricks platform, engineering, and architecture teams to ensure data products fully leverage the Lakehouse capabilities.

- Define product requirements for Lakehousebased ingestion, transformation, and consumption layers built on Databricks and Delta Lake.

- Drive adoption of Databricks features such as Delta Live Tables, Unity Catalog, Lakehouse Monitoring, and Workflows to ensure scalable, governed, and automated data products.

- Oversee design of domainoriented data products aligned with Medallion Architecture (Bronze/Silver/Gold).

- Ensure product roadmaps incorporate Databricks performance optimization strategies, including storage patterns, autoscaling, cluster policies, and cost governance.

- Collaborate with data modelers and engineers to shape semantic models and data contracts implemented within Databricks.

- Define data quality, validation, and governance requirements using Delta expectations, Unity Catalog lineage, and Databricks quality frameworks.

- Drive the enablement and adoption of Databricks SQL, dashboards, and semantic layer features to support analytics use cases.

- Partner with security and governance teams to enforce Unity Catalogbased access policies, entitlements, and compliance.

- Champion best practices for reusability, discoverability, and lifecycle management of Databricks-backed data products.

- Direct experience managing data products delivered on Databricks, Delta Lake, and Lakehouse architectures.

- Strong understanding of Databricks core services: Workflows, SQL Warehouses, Unity Catalog, MLflow, Delta Lake, and DLT.

- Knowledge of data quality and reliability frameworks such as expectations, schema evolution, and table optimization techniques (Zorder, file compaction).

- Familiarity with Databricks governance features including lineage, auditing, and fine-grained access control.

- Experience building or managing data products that rely on streaming pipelines using Spark Structured Streaming, Event Hubs, or Kafka.

- Understanding of how Lakehouse patterns support AI/MLenabled data product capabilities.

- Partner with data engineering, data science, analytics, and platform teams to deliver scalable data solutions.

- Ensure data products are consumable through dashboards and analytical assets built with Tableau, Power BI, or similar tools.

- Champion data quality, governance, and usability standards.

- Support user adoption, change management, and data literacy initiatives.

In addition to the qualifications listed below, the ideal candidate will demonstrate the following traits:

- Strategic and analytical mindset.

- Strong ability to extract and communicate actionable insights.

- Customer-centric and value-driven approach.

- Clear communication and stakeholder leadership.

- Ownership-driven decision making.

- Ability to operate in complex, cloud-based environments.

Minimum Qualifications:

- Bachelor s degree in Business, Engineering, Computer Science, Data Science, or related field.

- 10+ years of professional experience in product, data, analytics, or technology roles.

- Proven experience as a Senior Data Product Manager.

- Strong background in data analysis and insight extraction.

- Hands-on experience with BI tools such as Tableau or Power BI.

- Solid knowledge of cloud data platforms including Azure, AWS, and Databricks.

- Experience defining product roadmaps and backlogs for data products.

- Strong understanding of KPIs, metrics, data quality, and governance.

- Excellent stakeholder management and communication skills.

- Strong English verbal and written communication skills.

Preferred Qualifications:

- Experience with modern data architectures such as data warehouses or lakehouses.

- Familiarity with Agile/Scrum methodologies.

- Experience working with data engineering and data science teams.

- Knowledge of experimentation, A/B testing, or advanced analytics.

- Exposure to AI- or ML-enabled data products.

- Experience leading data adoption and change management initiatives.

- Relevant certifications in Product Management, Cloud, or BI platforms.