Lead Analyst

Dentsu Global Services; Bengaluru; Sur place; INR 1 800 000 - 2 400 000; Plein temps

Résumé du poste

Dentsu Global Services in Bengaluru is seeking a seasoned analytics leader to own end-to-end client problems—from framing the business question to delivering insights that influence decisions.

You will lead analytics, AI agent initiatives on Azure, Power BI reporting, and cross-functional teams, optimizing marketing performance data pipelines and governance.

Qualifications

• 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.

Responsabilités

• 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; 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.
• Lead analysis of campaign, channel and website performance using clickstream and marketing data (e.g., Adobe Analytics, GA4).
• 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.
• 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 – e.g., insight generation, anomaly detection, reporting commentary, analyst co-pilots.

Connaissances

Marketing analytics

Power BI

AI agents

Team leadership

Data integration

Outils

Azure AI Foundry

Copilot Studio

Semantic Kernel

LangChain

LangGraph

Microsoft Fabric

Data Factory

Notebooks

Medallion architecture

Adobe Analytics

GA4

Python

SQL

Description du poste

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.
• 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.
• 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; build the business case on cost, accuracy and effort.
• Monitor agent quality, cost (e.g., token usage) and responsible AI guardrails in production.

Team leadership and operational excellence

• 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.

Qualifications and skills

Must-have experience

• 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.

Tools and knowledge (preferred)

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.

Good to have

• 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.

Mindset, values and culture

Who you are

• Problem solver: you take ownership of the full problem and see it through.
• Learning mindset: you keep up with fast-moving AI and data tools and share what you learn with the team.
• Hands-on: you are comfortable building, not just reviewing.
• Cost-aware: you weigh value, effort and run cost before picking a solution.
• Clear communicator: you explain complex ideas simply to technical and business audiences.