Lead Analyst - Marketing Analytics

Job Description: Role at a glance Job title: Manager – Marketing Analytics & AI Solutions Level: Manager (DCF 40) Experience: 7+ years in marketing analytics / data & analytics Team: Leads a team of 8–10 analysts and engineers Location: India – BLR Purpose of the role We are looking for a hands-on Marketing Analytics Manager who can own business problems end to end – from understanding the client question, to building the data pipeline, to shipping the Power BI dashboard, AI agent or automation that answers it. The role blends marketing analytics, data engineering on Microsoft Fabric and applied AI, and leads a team of 8–10 people while keeping delivery and operational metrics on track. What makes this role different • End-to-end ownership: you own the outcome, not a single task in the chain. • Right tool for the job: you know when a simple automation beats an AI agent, and you choose the option that saves cost. • Player-coach: you lead the team and still roll up your sleeves on SQL, Python, Fabric and Power BI. 02 Key responsibilities End-to-end problem solving and consulting • Own client problems from start to finish: frame the business question, design the solution, build it, and land the insight with stakeholders. 2 Job Description – Manager – Marketing Analytics & AI Solutions – For internal use only • Act as a trusted advisor to client and internal stakeholders; translate marketing and business goals into clear data and analytics requirements. • Break down ambiguous, cross-functional problems instead of working on siloed tasks; connect data, reporting and AI into one solution. • Present findings and recommendations in a clear, simple, business-first way. Marketing analytics and insights • Lead analysis of campaign, channel and website performance using clickstream and marketing data (e.g., Adobe Analytics, media platforms). • Build and interpret funnel, journey, attribution and conversion analyses to drive optimisation decisions. • Define KPIs and measurement frameworks that link marketing activity to business outcomes. Data engineering and pipelines (Microsoft Fabric) • Manage ETL/ELT pipelines that ingest marketing and clickstream data from APIs, cloud apps and databases. • Apply Microsoft Fabric concepts – Lakehouse, OneLake, Data Factory pipelines, Notebooks and the Medallion (Bronze, Silver, Gold) architecture. • Enforce data quality, governance and documentation; keep pipelines reliable, performant and cost-effective. Power BI and reporting • Lead the design and build of Power BI dashboards and semantic models (data modelling, DAX, row-level security, performance tuning). • Move reporting from manual effort to automated, self-serve insight for business users. AI agents and intelligent automation • Identify use cases where AI agents add value – e.g., insight generation, anomaly detection, reporting commentary, analyst co-pilots.