---
title: "Smriti Sharma - Data Engineer in India | Tal"
description: "Meet Smriti Sharma, Data Engineer | Python | SQL | PySpark | Azure Data Factory | Databricks | ADLS Gen2 | ETL/ELT | Data Pipelines based in India. AI stack includes antigravity, claude code, and cursor."
image: "https://tal.club/meet/smriti-sharma-1/share-image"
---

# Smriti Sharma on Tal

## Headline

Data Engineer \| Python \| SQL \| PySpark \| Azure Data Factory \| Databricks \| ADLS Gen2 \| ETL/ELT \| Data Pipelines

## About

Data Engineer with 2\+ years of experience building ETL/ELT pipelines and working with data from APIs, CSV/Excel files, and business applications\. I work mainly with Python, SQL, PySpark, Apache Spark, Azure Data Factory, Azure Databricks, ADLS Gen2, Delta Lake, and Snowflake\. In my current role, I work on end\-to\-end data engineering solutions including data ingestion, transformation, data validation, reconciliation, incremental processing, and pipeline monitoring\. I have also worked with Medallion Architecture \(Bronze/Silver/Gold\) and configuration\-driven data processing for different client data structures\. Before moving into Data Engineering, I worked as a Backend Engineer where I developed Python/FastAPI services, REST API integrations, and data\-processing workflows using PostgreSQL and MongoDB\. I enjoy solving data integration and data\-quality problems and building reliable pipelines that can support analytics and downstream applications\. Core skills: Python \| SQL \| PySpark \| Apache Spark \| Azure Data Factory \| Azure Databricks \| ADLS Gen2 \| Delta Lake \| Snowflake \| ETL/ELT \| Data Pipelines \| Data Quality \| REST APIs

## Location

India

## AI stack

antigravity

claude code

cursor

deepseek

gemini

github copilot

## Work experience

Data Engineer at Excellence Integrity Management, May 2025 \- Present · 1 yr 5 mos, Bengaluru, Karnataka, India, Architected and deployed an end\-to\-end cloud data platform for an international OTT streaming client \("Wonder"\), centralizing fragmented user, content, and payment data\. Key Contributions: \- Built automated data ingestion pipelines using AWS Glue \(Python\), extracting streaming logs, viewing telemetry, and customer activities from REST APIs into Amazon S3 on a 4\-hour schedule\. \- Automated continuous file ingestion from S3 landing buckets into Snowflake RAW staging tables leveraging Snowpipe notifications\. \- Implemented a 3\-layer Medallion Architecture \(Raw → Silver → Gold\) via Snowflake Tasks and SQL to clean corrupted data types, resolve missing entity IDs, and standardize regional schemas\. \- Modeled an enterprise Star Schema \(Fact and Dimension tables\) in Snowflake, structurally resolving cross\-system reconciliation mismatches between Evergent billing feeds and video activity streams\. \- Spearheaded a storage and performance POC evaluating Parquet columnar formats and Snappy compression against raw CSV in S3, benchmarking warehouse scanning costs and analytical query performance\. \- Engineered automated source\-to\-target data validation mechanisms \(schema verification, null handling, and duplicate deduplication\) to guarantee data integrity across business dashboards\. Skills: Snowflake, AWS Glue, Amazon S3, Snowpipe, Snowflake Tasks, Medallion Architecture, Dimensional Modeling, Python, SQL

Back End Developer at triggerAll, Oct 2023 \- Feb 2025 · 1 yr 5 mos, India, Architected and scaled an omnichannel backend engine unifying inventory, manufacturing tracking, and order fulfilment across Amazon \(SP\-API\), Shopify, Etsy, and direct web channels\. Key Contributions: \- Engineered an event\-driven webhook processing layer with FastAPI and PostgreSQL, processing real\-time order streams with sub\-50ms gateway latency\. \- Eliminated multi\-channel race conditions and overselling by implementing pessimistic row\-level locks \(SELECT FOR UPDATE\) in PostgreSQL for concurrent checkouts\. \- Designed asynchronous outbound sync workers using Celery and Redis to navigate external API rate limits \(Amazon, Shopify\) with exponential backoff and jitter, reducing stock propagation latency under 2 seconds\. \- Formulated a Bill of Materials \(BOM\) relational schema to automate raw material deduction \(MDF sheets, acrylic, paints\) and forecast production restock cycles\. \- Integrated pre\-signed AWS S3 upload pipelines for custom engraving/photo assets, decoupling heavy payloads from transactional checkout flows\. Skills Used: Python, FastAPI, PostgreSQL, Redis, Celery, AWS S3, Docker, REST APIs, System Design

## Education

Bachelor of Technology \- BTech, Computer Science, Biju Patnaik University of Technology, Odisha

[View the original profile](https://tal.club/meet/smriti-sharma-1)

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