Senior BI & AI Engineer

We're looking for a hands-on BI & AI Engineer to join our Portfolio Management team in India. You'll own the full data-to-insight pipeline: building complex Power BI reports and Snowflake Dataflows that product and finance leadership rely on daily, and layering LLM-powered AI workflows on top to make that data conversational and actionable. This is an individual contributor role for someone who can move comfortably between writing DAX, querying Snowflake, automating business processes in Power Automate, and shipping Python-based agentic workflows with the Anthropic API, all within the context of portfolio reporting, financial planning, and resource management. About the role In this opportunity, you will be responsible for: Power BI & Data Reporting Design and maintain complex Power BI reports and dashboards for portfolio performance, financial actuals vs targets, and resource utilisation. Build and manage Power BI Dataflows and semantic models on top of Snowflake owning the full stack from ingestion to published report. Write advanced DAX: calculation groups, time intelligence, dynamic measures, row-level security. Optimise report performance and maintain documentation and data lineage across the BI estate. Data Engineering & Snowflake Query, transform, and model data in Snowflake building clean fact/dimension structures that feed both BI reports and AI layers. Write production-quality SQL and Python to automate data pipelines, replace manual file-based refreshes, and maintain data quality checks. Integrate data from sources such as SharePoint, SAP, Workday, Fieldglass, and Azure DevOps into governed reporting layers. AI & Agentic Workflow Development Build LLM-powered workflows using Claude (Anthropic API) and Claude Code enabling natural-language access to portfolio data, automated insight generation, and intelligent report summaries. Design and ship agentic pipelines that automate repetitive analysis tasks: data mapping maintenance, anomaly flagging, narrative generation for financial reports. Develop prompt engineering standards and evaluation frameworks to ensure AI outputs are accurate and reliable in a financial reporting context. Explore and implement AI-assisted approaches to ETL maintenance and transformation code generation. Automation & Process Improvement Build Power Automate flows to streamline data collection, approval workflows, and report distribution processes. Identify and eliminate manual, error-prone reporting processes replacing them with automated, auditable pipelines. Partner with Finance, Product Operations, and Product Engineering teams to gather requirements and deliver tools that save time. About you Youre a fit for the role if your background includes: Must-Have Skills Power BI advanced report building, Dataflows, semantic models, complex DAX, RLS, deployment pipelines. Snowflake schema design, complex SQL, data modelling, performance tuning, integration with Power BI. Python data engineering scripts, Pandas, REST API calls, automation. Comfortable writing code that runs in scheduled pipelines. LLM / Agentic AI hands-on experience shipping AI workflows using Claude, LangChain, LlamaIndex, or equivalent. Not just prompting actual applications in production or near-production. Power Automate building business automation flows integrated with Microsoft 365 and SharePoint. DAX & SQL strong command of both for analytical and engineering purposes. Domain context ability to work with financial data (actuals, targets, forecasts), portfolio tracking data, and resource/headcount data. Nice to Have Experience with DBT, Azure Data Factory, or Microsoft Fabric Notebooks for pipeline orchestration. Familiarity with Azure DevOps data (Work Items, iterations) as a portfolio execution data source. Exposure to vector databases, semantic search, or RAG architectures. Claude Code experience for AI-accelerated development workflows. Experience & Background 810 years of experience in BI engineering, data engineering, or analytics engineering. At least 3 years of hands-on Power BI development (reports + Dataflows + semantic models not just report building). At least 12 years of applied LLM or AI workflow development in a professional context, with something to show for it. Masters degree in computer science, Data Engineering, Information Systems, or equivalent experience. Whats in it For You Hy .