Senior Data Product Manager

About

Infinite is a global leader in technology modernization, next-gen IT services and solutions, and digital engineering, with over two decades of experience helping clients turn digital transformation into business value. Leveraging an AI-first approach, we combine leading technologies, innovative platforms and accelerators with practical know-how. With the scale of over 23,000 talented professionals across 20+ global locations, we proudly serve hundreds of clients, across all industries including healthcare, financial services, telecom, technology, media, and more.

At Infinite, we go beyond technology. We collaborate deeply with our clients to deliver innovative, tailored and client-focused solutions. Infinite is proud to be recognized by ISG, Avasant, Everest Group, HFS, Fosway Group and others for the innovation and leadership we bring to our clients.

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.