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kushal panthi

@kushalpanthi

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Analytics Engineer specializing in cloud-native data modeling, ELT, and trusted business-ready datasets.

United States

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What I'm looking for

I seek a hands-on role where I can design scalable cloud data platforms, improve data quality and observability, partner with stakeholders, mentor engineers, and drive measurable business impact.

I am an Analytics Engineer with 6+ years building cloud-native data models and pipelines across finance, healthcare, and retail. I specialize in SQL, dbt, and Python to deliver trusted, business-ready datasets, define metrics, and document lineage to enable self-service analytics at scale.

I have implemented orchestration with Airflow and ADF, optimized BigQuery/Snowflake/Synapse for cost and performance, and driven data quality using dbt tests and Great Expectations. I partner closely with stakeholders, mentor junior engineers, and deliver reliable, scalable solutions that empower analytics and downstream BI/ML teams.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Orion Capital Group

Apr 2023 - Present (2 years 5 months)

Designed and delivered dbt models and modular ELT pipelines in ADF and Airflow powering financial analytics; implemented dbt tests and Great Expectations to improve data reliability and optimized Synapse/Snowflake performance, reducing query cost and latency ~30%.

DBT SQL Airflow Azure Data Factory Snowflake Synapse Great Expectations Power BI CI CD

Data Engineer

Johnson & Johnson

Feb 2021 - Mar 2023 (2 years 1 month)

Built HIPAA-compliant ADF + Databricks pipelines ingesting EHR, claims, and trial data into Snowflake and developed curated dbt models with tests and documentation to enable patient analytics and downstream BI/ML use cases.

ADFS Databricks Snowflake DBT SQL Airflow Great Expectations Python

Data Engineer

Procter & Gamble

Mar 2018 - Oct 2020 (2 years 7 months)

Built SQL marts and Spark pipelines to unify global retail data, designed dimensional models for inventory analytics, migrated assets into ADLS/Hive and refactored into Snowflake, cutting onboarding time ~30%.