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Parthiv Chokshi

Parthiv Chokshi

Modern data engineer

Talent
VadodaraMember since June 25, 2026
SnowflakeVirtual WarehousesSnowpipeTime TravelRBACRow-Level SecurityData ModelingFact & Dimension TablesSCD TypesSnowflake Schemadbtdbt Coredbt ModelsAzure Data FactorySSISApache AirflowAWSLambdaS3IAMAWS GlueAzureAzure Cloud StorageVARIANTReal-time IngestionMedallion ArchitectureSQLPythonPowerShellGitHub
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SnowflakeVirtual WarehousesSnowpipeTime TravelRBAC

About

Results-driven Data Engineer with 2+ years of hands-on experience building scalable data pipelines, cloud data warehouses, and dimensional data models. Core expertise in Snowflake, dbt, Azure Data Factory, and AWS. Demonstrated ability to design and optimize ETL/ELT pipelines, implement data quality frameworks, and enable analytics-ready data across Staging, Integration, and Enterprise layers.

Experienced in Agile/Scrum environments with strong collaboration across data, analytics, and engineering teams.

Experience

Data Engineer at Insignyx Technologies (2024-02 – Present)

Designed, developed, and maintained end-to-end ETL/ELT pipelines using Snowflake, dbt, Azure Data Factory (ADF), SSIS, and AWS, supporting both batch and real-time ingestion patterns.

  • Built and optimized Snowflake data warehouses including virtual warehouse configuration, query performance tuning, clustering keys, and compute cost reduction of 15% through resource monitoring strategies.
  • Implemented dbt models across Staging, Integration, and Enterprise layers with incremental models, generic and singular data quality tests, source freshness checks, and auto-generated documentation.
  • Designed dimensional data models incorporating Fact and Dimension tables, SCD Type 1 and Type 2 handling, and schema design best practices aligned with Kimball methodology.
  • Developed Snowpipe pipelines for near real-time data ingestion from cloud storage, enabling continuous data availability for downstream analytics.
  • Applied Snowflake security best practices including RBAC (Role-Based Access Control) and Row-Level Security policies for data governance across multi-team environments.
  • Built scalable cloud data ingestion pipelines on AWS using Lambda, S3, and IAM, integrating with Snowflake as the target data warehouse.
  • Collaborated with business analysts, data scientists, and technical stakeholders to translate requirements into scalable data solutions; participated in Agile sprint ceremonies using Jira and Confluence.
  • Prepared technical documentation, code reviews on GitHub, and supported CI/CD best practices for pipeline deployment and version control.

Education

B.Tech in Mechanical Engineering – Babaria Institute of Technology (2022)

Skills

Modern data engineer

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