Oversee the design and deployment of Analytics solutions, including data integration, data management and data governance Collaborate with cross-functional teams to understand data requirements and develop scalable solutions Develop action plan to structure next steps / tasks, assign corresponding timelines, and create scrum teams with required skills  Ensure timely execution of agreed actionable and provide progress update to the Head of Analytics  Effective communication & negotiations with the internal customers to ensure successful execution with ownership  Solutioning the business needs / requirements, participate/ drive discussions with business  Ensure DevOps practices are followed during development and deployment  Participate in practice development to drive business growth and deliver data analytics solutions to business units  Lead implementation of enterprise & federated data lakes and Analytics solutions Ensure compliance to Group mandate of Data Governance principles  Skill and Experience Proven experience in leading large teams if data engineers & Data Scientists  Lead a team of technical professionals in the design, development and implementation of Analytics & Data Science solutions on cloud platforms   Stay abreast of emerging trends, technologies and industry developments in big data, cloud, AI/ML and GenAI  Develop and maintain best practices, standards and guidelines for Data Science projects like Feature store, model deployment, re-usable components  Collaborate with cross-functional teams including data scientists, data engineers, business analysts and stakeholders to define project requirements, objectives and timelines  Experience in delivering Analytics solutions using variety of data sources including semi-structured and unstructured data sources (image/video, GPS. IoT) Strong expertise in ETL/ELT processes, data lake, Datawarehouse, data mesh  Good knowledge of native data engineering services of Azure/GCP, scheduling and orchestration tools like Airflow, Composer Experience in deploying Machine Learning/AI workloads on Kubernetes clusters and as a PI endpoints  Strong analytical & problem-solving skills with the ability to think critically & creatively about complex business problems Strong communication skills Good knowledge of DevOps practices and tools Education Qualification Master’s/bachelor’s degree in engineering/management from premier institutes  Professional certification in Azure, GCP, Databricks, AI/ML