Power BI · Python · SQL · Renewable Energy Markets
10+ years across renewable energy forecasting & scheduling, open access, DSM accounting and power trading — turning raw generation and market data into dashboards, KPIs and decisions that protect revenue and improve asset performance.
I'm a data and BI analyst working in the renewable energy sector — forecasting & scheduling, open access, DSM accounting and settlement, and power trading support for wind and solar generators. My day-to-day is real-time operational data: cleaning it, modelling it, and putting it in front of the people who act on it.
I build Power BI dashboards and automated reporting pipelines with Power Query, Python and SQL, and I'm currently deepening my data engineering stack with Microsoft Fabric (DP-600 and DP-700 in progress) — lakehouse, dataflows, pipelines and medallion architecture. Next on the list: BESS and green hydrogen.
10+
Years of Experience
50+ GW
Portfolio Analysed
15%
Forecast Accuracy Gain
30%
Manual Effort Reduced
Skills
Tools I Build & Deliver With
Business Intelligence
Power BIData VisualizationKPI DevelopmentDashboardingData Storytelling
Leading data-driven forecasting, scheduling and open access operations for wind and solar assets using real-time datasets — tracking KPIs, managing DSM and deviation analytics, and driving data standardization on modern platforms like Microsoft Fabric.
Built Power BI dashboards tracking generation trends, forecast accuracy, DSM impact and revenue across a 50+ GW portfolio; automated reporting with Power Query (−30% manual effort) and improved forecasting accuracy by 15%.
Power BIPower QueryIEX BiddingData CleaningReporting Automation
Project Engineer (Contract)
NTPC / IOCL Projects (NBPPL & EIL)
2017 – 2019
Contributed to large-scale power and refinery projects, gaining exposure to operations, data capture and structured project reporting processes.
Project EngineeringOperationsReporting
Assistant Engineer – Wind Operations
Wind World India Ltd., Mumbai
Jul 2013 – May 2016
Used data analysis to improve wind farm productivity by 25%, producing MIS reports and running trend analysis, benchmarking and root cause analysis on operational performance data.
Wind OperationsMIS ReportingTrend AnalysisRoot Cause Analysis
Portfolio
Selected Work
Analytics and reporting built for real energy operations — with measurable outcomes.
Power BI · Renewables
Generation & Revenue Performance Dashboard
Kreate Energy
A single Power BI model tracking generation trends, forecast accuracy, DSM impact and revenue across a 50+ GW portfolio — replacing scattered spreadsheets with one governed daily view for commercial and operations teams.
Rebuilt manual Excel reporting as a Power Query pipeline with repeatable cleaning, validation and transformation steps — cutting manual reporting effort by 30% and removing a recurring source of keying errors.
Analysed historical generation and deviation data to identify systematic forecast bias by site and time block, feeding corrections back into the scheduling process and improving accuracy by 15%.
Structured DSM accounting and settlement data into a reconcilable model — surfacing deviation penalties by asset and period so commercial teams could target the sites driving financial leakage.
Data-backed bidding support for IEX day-ahead and real-time markets — price and volume trend analysis paired with portfolio availability to inform bid strategy.
Coordinated captive power allocation for open access projects with tracked regulatory timelines — keeping allocation, banking and grid connectivity compliance auditable across sites.
Open AccessCaptive AllocationRegulatory ComplianceEnergy Banking
Microsoft Fabric · Learning
Lakehouse & Medallion Architecture Build-Out
Self-Directed (DP-600 / DP-700)
Hands-on Microsoft Fabric work — dataflows, lakehouse tables, pipelines and Power BI integration structured as Bronze / Silver / Gold layers, as preparation for DP-600 and DP-700.
Microsoft FabricLakehouseDataflows Gen2Medallion Architecture
Wind Operations
Wind Farm Productivity Analysis
Wind World India
Performance benchmarking and root cause analysis across turbines using operational and SCADA data, driving a 25% improvement in wind farm productivity.
A Bronze–Silver–Gold Fabric Lakehouse replacing a five-join 3NF warehouse — metadata-driven batch and incremental ingestion, PySpark curation, and a pre-aggregated Gold star schema served to Power BI in Direct Lake mode.
Medallion ArchitectureStar SchemaPySparkSurrogate KeysPower BI Direct Lake
Microsoft Fabric · Retail Inventory
On-Premises PostgreSQL Migration to Fabric Lakehouse
RetailCore Ltd
Replaced a fragile daily CSV export with a gateway-secured Fabric pipeline that copies the full PostgreSQL inventory snapshot into a governed Lakehouse Delta table — overwrite loads, schema enforcement and a timestamped audit record per run.
On-premises Data GatewayPostgreSQLCopy DataDelta TableAudit Logging
Microsoft Fabric · Market Risk
Market Risk Intelligence Feed — FX Rate Ingestion & Backfill
Global Credit Corp
Replaced manually keyed spreadsheet FX rates with a warehouse-native Fabric feed — REST API calls, T-SQL OPENJSON parsing, and an idempotent stored procedure that supports safe replay and historical backfill.
Financial Data Transformation Using PySpark & Delta Lake
Global Corp
Re-engineered a two-hour AR aging join into a minutes-long Fabric notebook — broadcast joins to kill the shuffle, strict Delta schemas to block corrupted currency values, and Time Travel plus RESTORE for one-command recovery.
Enterprise Data Trust Transformation via Dataflow Gen2
TelcoPrime
A low-code Dataflow Gen2 quality layer for Customer 360 — governed lookup tables standardizing states and address suffixes, validated phone formatting, an engineered Data Quality Flag, and a trusted Silver table refreshed daily.
Bronze-to-Silver Fabric pipeline moving Azure SQL HR data into a governed Lakehouse — quarantining invalid rows, deduplicating employees, and enriching with department context for trusted workforce analytics.
Intelligent Landing Zone Orchestration — Dynamic Routing Framework
City of Metropolis
One metadata-driven Fabric router pipeline that classifies datasets by configuration, loads valid files into the Bronze Lakehouse, quarantines the invalid, archives the processed — and leaves an empty inbox every cycle.
Watermark-driven Fabric pipeline that detects new shipment JSON files, loads only incremental records into a governed Delta Lake ShippingLogs table, and advances its own state per run.
Fabric PipelineDelta LakeWatermark TableLookupCopy Data
Microsoft Fabric · Real Estate
Global Listing Intelligence Initiative
Grandeur Properties International
Replaced 24–48 hour manual CSV consolidation across London, Dubai and New York with an automated, governed Fabric Lakehouse pipeline delivering trusted data by 7:00 AM.
Delta LakeDelta Live TablesUnity CatalogWorkflowsSQL Warehouses
Contact
Let's talk energy data.
Open to data analyst, BI and energy analytics roles — especially with renewable generators and developers. Reach out and I'll get back within a business day.