Lead Analyst - Marketing Analytics

Overview

Lead a team of 8–10 analysts and engineers to own marketing analytics and AI solution problems end to end, from framing the business question through data pipelines and Power BI dashboards to AI agents or automation, while keeping delivery and operational metrics on track.

What you'll do

• Own client problems from start to finish: frame the business question, design the solution, build it, and land the insight with stakeholders.
• Act as a trusted advisor to client and internal stakeholders, translating marketing and business goals into clear data and analytics requirements.
• Break down ambiguous, cross-functional problems and connect data, reporting and AI into one solution.
• Present findings and recommendations in a clear, simple, business-first way.
• 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.
• 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.
• 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.
• Identify use cases where AI agents add value, such as insight generation, anomaly detection, reporting commentary and analyst co-pilots.
• Design, build and deploy AI agents, preferably on Azure AI Foundry, integrated with Fabric data and Power BI.
• Judge when rule-based automation (scripts, scheduled pipelines, Power Automate) is the better and cheaper choice than an agent, and build the business case on cost, accuracy and effort.
• Monitor agent quality, cost (e.g., token usage) and responsible AI guardrails in production.
• Lead, coach and grow a team of 8–10 analysts and engineers; set clear goals, review work and build skills in AI and Fabric.
• Own operational metrics: utilisation, on-time delivery, SLA adherence, quality/rework, backlog health and client satisfaction.
• Plan capacity, allocate work and manage risks and escalations across multiple workstreams.
• Drive process improvements, reusable assets and automation that raise team productivity.

What you'll need

• 7+ years of experience in marketing analytics, digital analytics or data & analytics roles.
• Proven experience managing ETL/ELT data pipelines end to end.
• Strong hands-on experience building Power BI dashboards and data models.
• Hands-on experience building or deploying AI agents or LLM-based solutions, with a clear view on when automation is the cheaper option.
• Experience leading a team of 8–10 people and managing operational metrics.
• Consulting or client-facing experience, ideally in an agency or professional services setting.

Nice to have

• AI agents: Azure AI Foundry (preferred); exposure to Copilot Studio, Semantic Kernel or LangChain/LangGraph is a plus.
• Microsoft Fabric: Lakehouse, OneLake, Data Factory pipelines, Notebooks, Medallion architecture.
• Clickstream: Adobe Analytics and/or GA4, including raw hit-level data (data feeds / BigQuery export).
• Marketing analytics: campaign performance, attribution, funnel and journey analysis.
• Power BI: data modelling, DAX, semantic models, performance tuning.
• Python and SQL: data manipulation (pandas, PySpark) and advanced SQL.
• Microsoft certifications such as DP-600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer) or AI-102 (Azure AI Engineer).
• Exposure to Azure Databricks, Alteryx or similar ETL tools.
• Understanding of consent, privacy and data governance in marketing data.

Details

• Location: DGS India - Bengaluru - Manyata N1 Block (India – BLR).
• Level: Manager (DCF 40); full time, permanent.