I don't just analyse data — I build the pipelines that collect it, the models that structure it, and the dashboards that make it actionable.
Four core capability areas — from raw ingestion to business decision. I operate across all of them.
Designing and building automated data pipelines that move, transform, and land data reliably — from API integrations to ETL workflows. If the data doesn't flow, nothing else works.
Complex querying, data modelling, and analytical frameworks that surface the signal in the noise. I write SQL that doesn't just run — it answers the right questions.
Interactive dashboards and self-serve analytics that translate complex data into clear decisions for leadership, operations, and finance teams. Built to be trusted and used daily.
Layering LLMs, vector search, and OCR on top of data pipelines to unlock intelligence that pure analytics can't reach — from automated insight generation to financial discrepancy detection.
Real work, real impact. Each project reframes a data problem into a business outcome.
Standardised and analysed 8 years of multilingual learner survey data to enable longitudinal insights, trend analysis, and data-driven program evaluation. Built a reusable processing pipeline that made years of messy, inconsistent data analytically sound for the first time.
Built interactive Tableau dashboards that transformed operational and learner data into trusted, self-serve insights for Finance, Operations, and Leadership. Replaced ad-hoc data requests with always-on visibility that leaders could trust and act on independently.
Designed and built a secure, API-driven ETL pipeline to automate data ingestion from the LMS into Salesforce, eliminating 100+ hours of manual data entry annually. Identified the $10K problem, scoped the solution, built the pipeline, and owned the outcome.
Applied AI-based OCR to automatically extract, parse, and validate vendor invoice data — identifying ~$9K in billing discrepancies that had gone undetected. Turned a manual, error-prone finance process into an automated analytical check with immediate ROI.
Built a privacy-first analytics and AI pipeline that converts raw learner survey data into actionable, personalised insights for instructors. Replaced gut-feel program planning with evidence-based decisions at scale.
Side projects that show how I think about data problems — financial modelling, reward optimisation, and decision tooling built from scratch.
An end-to-end analytics product that analyses user spending behaviour to surface optimised credit card matches and reward strategies. I designed the data logic and decision framework that translates complex rewards structures into clear, personalised recommendations — evaluating category spend, reward multipliers, and annual fee tradeoffs to maximise net value.
A financial analytics tool that estimates point accrual and transfer value for users in the Bilt ecosystem. The calculator models multiple earning scenarios — incorporating rent size, category spend, and transfer partner valuations — to project annual reward outcomes. I designed the underlying calculation engine to simplify complex loyalty math into an intuitive, decision-ready interface.
I've spent 4+ years at the intersection of data, systems, and business outcomes — building pipelines that didn't exist, dashboards that got used, and analytical frameworks that drove real decisions.
My background spans data engineering, BI, applied AI, and financial modelling. I'm comfortable in the terminal, in Tableau, and in the boardroom.
If you're looking for a Senior Data Analyst who can build the full stack — pipelines, models, dashboards, and decisions — I'd love to hear from you.
sreeharsha@sreeharshadakkili.com →