Choudhury P.

🎓 Academy Graduate

Senior Data Engineer

India5+ years experienceAvailable now$7,000/mo

Compare at US rates $21,000/mo?

Notable Highlight

Supported e-commerce and DTC businesses across Shopify, Amazon, Meta Ads, Pinterest Ads, and Klaviyo, with client exposure spanning beauty, skincare, and apparel.

Experience Summary

Choudhury Durga is a Senior Data Engineer with 5+ years of experience specializing in data engineering, cloud infrastructure, ETL development, API integrations, and data pipeline architecture. His core technical stack includes Python, SQL, and PySpark, complemented by experience across AWS, GCP, and Azure, with certifications across all three major cloud platforms. He has worked across data pipelines, cloud environments, APIs, ETL/ELT workflows, and modern data platforms.

Key Achievements

Built a US-based application from scratch at ST, contributing to the product's underlying application and data infrastructure.
Integrated AI/ML workflows into a production application, demonstrating experience applying AI/ML capabilities within a real product environment beyond traditional data engineering.
Developed Python-based REST APIs and ETL connectors for e-commerce clients, supporting data integration and automated data movement across platforms and systems.
Built and managed cloud-based data pipelines across AWS, GCP, and Azure with hands-on experience in all three environments.
Supported e-commerce and DTC businesses across platforms including Shopify, Amazon, Meta Ads, Pinterest Ads, and Klaviyo, with client exposure spanning beauty, skincare, and apparel.
Earned certifications across AWS, GCP, and Azure, enabling work across different client technology environments.
Managed multiple concurrent contract engagements, supporting two companies simultaneously while maintaining a demanding workload.
Developed broad data engineering expertise combining Python, SQL, PySpark, cloud engineering, Snowflake, dbt, API development, ETL, and AI/ML workflows.

Skills

SnowflakedbtApache AirflowPythonSQLPySparkScalaApache SparkApache BeamHiveBigQueryDataflowPub/SubCloud ComposerAWS GlueAmazon S3Amazon RedshiftDynamoDBAzure Synapse AnalyticsAzure Data FactoryDatabricksAzure Key VaultDelta LakeFivetranAirbyteSnapLogicREST APIsGitHub Actionsdbt CloudAppFlowDimensional ModelingStar/Snowflake SchemaIncremental ModelingSchema ContractsData GovernanceData LineageData Quality ControlsLookerTableauPower BISigma ComputingGitClaude CodeCodexCursorGeminiAzure MonitorLog AnalyticsRBACCloud FunctionsCloud RunBlue Yonder

Work Experience

Senior Data Engineer

a previous company · Remote · Nov 2025 - Present

Architected a governed staging-to-presentation dbt model layer on Snowflake with enforced schema contracts to become the single source of truth for GMV, ARR, and payments across 3 product brands.
Advanced daily data SLAs to before business hours across 150+ orchestrated Snowflake tasks by rebuilding ingestion through Fivetran, AWS Glue, S3, AppFlow, and GitHub Actions CI/CD.
Cut model delivery time 2-3x on complex builds by driving an AI-assisted engineering workflow (Claude Code, Codex) inside a peer-reviewed, production-grade pipeline.
Increased self-serve analytics adoption org-wide by replacing fragile Looker-derived tables with a governed semantic layer and standardizing metric definitions with finance and sales leadership.

Analytical Data Engineer

a previous company · Remote · Mar 2026 - Present

Eliminated a double-counting defect distorting lounge-occupancy revenue forecasts by re-architecting flight-schedule and visit data into governed 15-minute aggregate pipelines for the data science team.
Cut release regressions by embedding production-calibrated dbt testing macros directly into CI/CD via GitHub Actions and dbt Cloud.
Standardized lounge satisfaction scoring across global markets by versioning survey weighting logic and resolving systemic locale and join defects.
Simplified the platform architecture by migrating ingestion off SnapLogic and establishing dbt as the single transformation and orchestration layer on Snowflake.

Analytics Engineer

BYSCIF · Remote · Nov 2025 - Jan 2026

Stabilized production pipelines post go-live, reducing operational noise and manual intervention by diagnosing data quality and performance issues across Snowflake and Airflow.
Improved planning analytics turnaround for Merch and Demand Planning teams by designing optimized Snowflake data models integrated with Blue Yonder.
Shortened production fix turnaround by applying AI-assisted debugging (Codex, Cursor) to SQL and pipeline diagnostics without compromising production standards.

Data Engineer II / Analytical Data Engineer II

STS · Remote · Sep 2023 - Sep 2025

Delivered near real-time analytics for global retail and marketing clients, sustaining 99%+ data accuracy through end-to-end validation and reconciliation on GCP (BigQuery, Dataflow, Pub/Sub, Cloud Composer).
Improved query performance and warehouse cost efficiency by tuning complex SQL and building optimized Snowflake and BigQuery models for large retail datasets.
Accelerated new data-source onboarding by developing modular dbt transformation logic and deploying custom REST API connectors via Airbyte on Cloud Functions and Cloud Run.
Increased development velocity without compromising reliability by integrating Gemini into daily Python, SQL, and dbt development workflows.

Data Engineer I

KP · Remote · Jul 2022 - Jul 2023

Reduced manual reporting effort by building automated ETL pipelines with Apache Airflow, Python, and AWS.
Supported growing multi-user analytics workloads by designing scalable data models across BigQuery, Snowflake, and DynamoDB.
Protected downstream analytics integrity by implementing data quality checks and monitoring across ETL workflows.

Associate Professional Software Engineer

DT · India · Aug 2021 - Jun 2022

Supported enterprise analytics workloads by building pipelines with Azure Data Factory and Databricks, and optimizing storage via Azure Synapse Analytics and Delta Lake.
Met enterprise security and compliance requirements by implementing Azure Key Vault and RBAC across analytics environments.
Reduced downtime by monitoring and resolving pipeline issues via Azure Monitor and Log Analytics.