Head - Product

Product Head for Data, Analytics and Platform

Role Overview:

Product Head - Data and Analytics

Key Responsibilities:

1. Define and drive the

   strategic direction

   for data platforms, aligning technical initiatives with business goals and objectives.
2. Set clear

   OKRs

   (Objectives and Key Results) for data platform development and ensure alignment across all teams (engineering, data science, analytics, etc.).
3. Establish and enforce

   standards for planning

   , project management, execution, and documentation throughout the product lifecycle.
4. Lead the design and implementation of scalable

   data pipelines

   ,

   data lakes

   , and

   real-time analytics

   architectures, ensuring robust performance, security, and compliance.
5. Collaborate with

   Data Science

   ,

   Analytics

   ,

   Platform

   , and

   AI teams

   to ensure seamless integration of machine learning models, predictive analytics, and AI technologies.
6. Set and maintain high standards for

   project management

   , ensuring initiatives are delivered on time, within scope, and on budget, using Agile methodologies.
7. Ensure thorough

   documentation

   of technical processes, product specifications, and architectural decisions to maintain transparency and scalability.
8. Implement strong

   data governance

   and security protocols, ensuring compliance with relevant data protection regulations (GDPR, CCPA).
9. Develop key

   performance metrics

   (KPIs) to assess the success of data products and continuously iterate for improvement.
10. Mentor and lead product managers and technical teams, instilling a culture of ownership, innovation, and excellence in execution.

Qualifications:

1. BTech and/or MBA from top-tier colleges

   (e.g., IITs, NITs, ISBs, IIMs, or equivalent).
2. 10+ years of experience in

   product management

   , with a focus on building

   data platforms

   and integrating

   advanced analytics

   .
3. Proven track record in setting and executing

   strategic roadmaps

   ,

   OKRs

   , and ensuring business alignment across teams.
4. Deep understanding of

   cloud technologies

   (e.g., AWS, Azure) and familiarity with

   data frameworks

   (Hadoop, Spark, Kafka).
5. Strong experience with

   data architectures

   (data lakes, data warehouses, NoSQL/SQL), data governance, and

   real-time data pipelines

   .
6. Experience in integrating

   AI/ML models

   into data products and driving

   business intelligence (BI)

   initiatives (e.g., Tableau, Power BI).
7. Solid

   program management

   expertise with the ability to lead cross-functional teams and deliver complex projects on schedule.
8. Proven ability to set and maintain

   standards for planning

   , project management, and

   documentation

   to ensure high-quality execution.
9. Knowledge of

   data governance

   frameworks and experience ensuring compliance with regulations like GDPR, CCPA.
10. Excellent leadership, communication, and interpersonal skills, with the ability to engage and align technical and business stakeholders.