DGS India - Bengaluru - Manyata N1 Block / Insights & Analysis

Merkle Inc.; Bengaluru; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Merkle Inc. in Bengaluru, India invites a hands-on Manager for Marketing Analytics & AI Solutions to own client problems end-to-end — from framing questions to shipping Power BI dashboards and AI-enabled solutions.

You will lead a team of 8–10 analysts and engineers, blending marketing analytics, data engineering on Microsoft Fabric, and applied AI to deliver measurable business outcomes. The role requires 7+ years in marketing analytics, strong data pipeline and dashboard skills, and experience

Qualifications

• 7+ years in marketing analytics or data & analytics roles.
• Proven experience building 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.

Responsibilities

• 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 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, business-first way.
• Lead analysis of campaign, channel and website performance using clickstream and marketing data.
• 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 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 – 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 is the better and cheaper choice than an agent; build the business case on cost, accuracy and effort.
• Monitor agent quality, cost and 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.

Skills

Marketing analytics

Data pipelines

Power BI

AI agents/LLMs

Team leadership

Client facing

Education

Bachelor's degree in a relevant field

Tools

Azure AI Foundry

Microsoft Fabric

Power BI

Adobe Analytics

SQL

Python

Job description

About the job

Role at a glance

Job title: Manager – Marketing Analytics & AI Solutions

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.

Key responsibilities

• 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, 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 – 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.
• 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

• 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

• 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.