Product Manager - Data Management

About the Role

• Develop and execute a comprehensive strategy for 3rd party data platform adoption and expansion across the organization, with a focus on driving business outcomes and improving marketing effectiveness.
• Collaborate with marketing teams to integrate 3rd party data into their campaigns and workflows and provide training and support to ensure effective use of the data.
• Develop and showcase compelling use cases that demonstrate the value of 3rd party data in improving marketing effectiveness and measure the success of these use cases through metrics such as adoption rate, data quality, and marketing ROI.
• Develop and maintain a roadmap for 3rd party data platform adoption and expansion across the organization, with a focus on expanding use cases and applications for 3rd party data and developing new data-driven products and services.
• Monitor and measure the effectiveness of 3rd party data in driving business outcomes, and adjust the adoption strategy accordingly
• Work with cross-functional teams to ensure data quality and governance, and develop and maintain relationships with 3rd party data vendors to ensure seamless data integration and delivery.
• Drive the development of new data-driven products and services that leverage 3rd party data, and collaborate with stakeholders to prioritize and develop these products and services.
• Shift Timings: 2 PM to 11 PM (IST).
• Work from office for 2 days in a week (Mandatory).

About You

• 12+ years of experience in data management, product management, or a related field.
• Bachelors or Masters degree in Computer Science, Data Science, Information Technology, or a related field.
• Experience with data management tools such as data warehousing, ETL (Extract, Transform, Load), data governance, and data quality.
• Understanding of the Marketing domain and data platforms such as Treasure Data, Salesforce, Eloqua, 6Sense, Alteryx, Tableau and Snowflake within a MarTech stack.
• Experience with machine learning and AI frameworks (eg, TensorFlow, PyTorch).
• Expertise in SQL and Alteryx.
• Experience with data integration tools and technologies such as APIs, data pipelines, and data virtualization.
• Experience with data quality and validation tools and techniques such as data profiling, data cleansing, and data validation.
• Strong understanding of data modeling concepts, data architecture, and data governance.
• Excellent communication and collaboration skills.
• Ability to drive adoption and expansion of D&B data across the organization.
• Certifications in data management, data governance, or data science is nice to have.
• Experience with cloud-based data platforms (eg, AWS, GCP, Azure) nice to have.
• Knowledge of machine learning and AI concepts, including supervised and unsupervised learning, neural networks, and deep learning nice to have.