Job
Description
As a Technical Project Manager in Data Analytics, you will be responsible for owning analytics projects from client requirement understanding to technical execution and delivery. Your key responsibilities will include: - Client Interaction & Requirement Understanding: - Lead client calls, requirement discussions, and review meetings. - Convert client business use cases into clear analytics and technical requirements. - Prepare and maintain requirement documents, dashboard specs, and acceptance criteria. - Act as the primary point of contact for analytics delivery with the client. - Solution Design & Technical Ownership: - Design analytics solutions including data ingestion, transformation, KPI definitions, data modeling, and BI layers. - Provide technical direction to Data Analysts and Engineers. - Review SQL queries, transformations, and dashboard logic for correctness and performance. - Support architectural decisions while considering cost, scale, and timelines. - Project Execution & Delivery: - Own the complete delivery lifecycle from requirement to deployment. - Break requirements into clear tasks and manage execution using tools like Jira. - Track progress, dependencies, and risks; escalate proactively when needed. - Ensure deliveries meet agreed timelines and quality expectations. - ETL, Data Modeling & Quality: - Guide teams on ETL strategies and data quality checks. - Oversee schema evolution, data refresh logic, and handling of data issues. - Ensure delivered data is reliable, consistent, and analytics-ready. You must have the following skills and experience: - Strong experience in data analytics and BI project delivery. - Hands-on experience with BI/visualization tools such as Power BI, AWS QuickSight, Tableau, Google Looker Studio. - Experience defining business KPIs, metrics, and dashboard layouts. - Strong SQL skills, working knowledge of Python, and understanding of data warehouse modeling concepts. - Experience managing client-facing analytics projects and strong communication skills. Additionally, it would be good to have a basic understanding of data security concepts and experience working with US/Europe clients. As a Technical Project Manager in Data Analytics, you will be responsible for owning analytics projects from client requirement understanding to technical execution and delivery. Your key responsibilities will include: - Client Interaction & Requirement Understanding: - Lead client calls, requirement discussions, and review meetings. - Convert client business use cases into clear analytics and technical requirements. - Prepare and maintain requirement documents, dashboard specs, and acceptance criteria. - Act as the primary point of contact for analytics delivery with the client. - Solution Design & Technical Ownership: - Design analytics solutions including data ingestion, transformation, KPI definitions, data modeling, and BI layers. - Provide technical direction to Data Analysts and Engineers. - Review SQL queries, transformations, and dashboard logic for correctness and performance. - Support architectural decisions while considering cost, scale, and timelines. - Project Execution & Delivery: - Own the complete delivery lifecycle from requirement to deployment. - Break requirements into clear tasks and manage execution using tools like Jira. - Track progress, dependencies, and risks; escalate proactively when needed. - Ensure deliveries meet agreed timelines and quality expectations. - ETL, Data Modeling & Quality: - Guide teams on ETL strategies and data quality checks. - Oversee schema evolution, data refresh logic, and handling of data issues. - Ensure delivered data is reliable, consistent, and analytics-ready. You must have the following skills and experience: - Strong experience in data analytics and BI project delivery. - Hands-on experience with BI/visualization tools such as Power BI, AWS QuickSight, Tableau, Google Looker Studio. - Experience defining business KPIs, metrics, and dashboard layouts. - Strong SQL skills, working knowledge of Python, and understanding of data warehouse modeling concepts. - Experience managing client-facing analytics projects and strong communication skills. Additionally, it would be good to have a basic understanding of data security concepts and experience working with US/Europe clients.
