Amrit Pattnaik

Data Analyst with over 3 years of experience specializing in agricultural data operations and geospatial data validation at AryaTech Platforms Pvt. Ltd. (Arya.ag). Proficient in leveraging Snowflake as the exclusive cloud data platform to ingest, clean, transform, and manage large-scale data workflows.

Recently focused over the last 3–4 months on executing core Snowflake operations, including FPO database record management, critical application query resolutions via Time Travel, and writing optimized SQL aggregation scripts to generate reporting summaries. Expert at bridging manual field-mapping processes with enterprise cloud analytics to ensure total database consistency and data accuracy natively within Snowflake Worksheets.

Data Augmenter – I (Data Analyst) at AryaTech Platforms Pvt. Ltd. (Arya.ag) (2022-10 – Present)

Transitioned to using Snowflake extensively for backend agricultural data management, database auditing, quantitative data cleaning, and daily operational reporting workflows.

• FPO Record Management & Synchronization: Wrote SQL update and insert queries natively in Snowflake to handle end-to-end data management for Farmer Producer Organisations (FPOs), keeping daily farmer profiles, mobile numbers, and Organization IDs (Org_IDs) accurate and duplicate-free to increase business efficiency.
• AryaShakti Query Resolution: Resolved daily application query issues—such as tracking down accidental record deletions or incorrect data entries by users—by leveraging Snowflake's Time Travel (AT / BEFORE) feature to look at past data states and safely restore the original records.
• Vikshep Data Summary Generation: Programmed high-performance SQL aggregate queries (using COUNT, SUM, JOIN, and GROUP BY) inside Snowflake to compress thousands of raw rows into clean, regional summary data tables displayed on dashboards to facilitate satellite-monitoring of farms.
• Enterprise Cloud Ingestion: Managed the technical pipeline to load field-digitized farm boundaries (exported from Google My Maps and Google Earth as KML files and converted to GeoJSON strings) directly into Snowflake landing tables.
• Native Geospatial Transformation: Executed Snowflake's native TO_GEOGRAPHY() function to change raw GeoJSON text strings into live map objects, allowing the database to read and process the shapes for accurate geospatial visualization.
• Automated Quality Assurance: Developed SQL scripts using ST_INTERSECTS and ST_CONTAINS in Snowflake to programmatically run overlap detection and coordinate validation checks across mapped farm polygons.
• Acreage Calculation & Checking: Used ST_AREA inside Snowflake Worksheets to calculate exact plot dimensions in square meters, converting the numbers into Acres using SQL multipliers to verify reported farm data.
• Metadata Management for AI/ML: Organized and structured agricultural data tables in Snowflake to keep track of crop contours and grain labeling datasets (wheat, rice, maize, chana) annotated using Roboflow.

M. Tech in Power Systems Engineering – Odisha University of Technology and Research (Formerly, CET) (2018-07 – 2020-06)

B. Tech in Electrical Engineering – Biju Patnaik University of Technology (2014-07 – 2018-05)