Pallavi  ·  Senior Snowflake Data Engineer  ·  5+ yrs

Mid-Level
Bengaluru5+ years experienceremote
Available within 48 hrs

About Pallavi

Pallavi is a skilled Data Engineer with extensive experience in developing and optimizing data pipelines. She has a strong background in cloud platforms such as AWS, GCP, and Azure, and is proficient in various technologies including Python, SQL, and Snowflake. Pallavi has successfully led multiple data migration projects and implemented CI/CD pipelines to enhance data processing efficiency. Her focus on data quality assurance ensures that the data integrity is maintained across all projects.

Core expertise

Python
language
9/10
SQ
SQL
database
9/10
Snowflake
database
9/10
AI
Airflow
devops
9/10
DB
DBT
devops
9/10
PySpark
other
8/10
RE
Redshift
database
8/10
BI
BigQuery
database
8/10
AG
AWS Glue
other
8/10
AD
Azure Data Factory
devops
8/10

Additional skills(17)

PythonPySparkSnowflakeAzure DatabricksGitHub ActionsHadoopGCPSQL ServerGITSQL

Why hire Pallavi?

Production deploy authorityLed multiple data migration projectsStrong focus on data quality assurance

Led the adoption of DBT to streamline end-to-end data engineering workflows.

Successfully transitioned data processing from SQL queries on Redshift to AWS Glue jobs, improving ETL efficiency.

Implemented CI/CD pipelines for data warehousing and automated data processing using GitHub Actions.

Developed robust integration pipelines on Azure Data Factory and implemented PySpark jobs on Azure Databricks.

Migrated merchandising data from Hadoop to Google Cloud Platform (GCP), optimizing processes with Jenkins and Apache Airflow Composer, reducing processing time by 25%.

Implemented Business Intelligence solutions involving data migration from SQL Server to GCP BigQuery, ensuring data integrity through rigorous quality checks.

Project highlights(6)

Data Transformation Strategy Enhancement – Data Engineer

Overview: This project involved transitioning data processing from Redshift SQL queries to AWS Glue jobs, aiming to improve ETL efficiency for a retail company. Responsibilities: Successfully transitioned data processing from SQL queries on Redshift to AWS Glue jobs, significantly improving ETL processes. Developed PySpark jobs for transformation and aggregation reports, enhancing data processing efficiency. Implemented integration pipelines with various data sources using AWS Glue.

PythonSQLRedshiftAWS GluePySpark

Key outcomes:

  • Successfully transitioned data processing from SQL queries on Redshift to AWS Glue jobs, significantly improving ETL processes.

End-to-End Data Engineering Workflow Optimization – Data Engineer

Overview: This project focused on optimizing data processing and engineering workflows using modern tools and methodologies for a retail company, specifically leveraging DBT. Responsibilities: Led data processing initiatives using DBT, overseeing the complete end-to-end data engineering workflow. Wrote code for ETL processes in Snowflake, ensuring seamless data flow from raw to transformed to aggregated layers.

DBTSnowflakeAirflowSQL

Key outcomes:

  • Streamlined end-to-end data engineering processes by leading the adoption of DBT.

Integration Pipeline and Automation – Data Engineer

Overview: This project focused on streamlining data integration and automating processing tasks for a retail company using Azure services. Responsibilities: Developed integration pipelines on Azure Data Factory, ensuring smooth data flow. Implemented PySpark jobs for data transformation on Azure Databricks, enhancing processing efficiency.

Azure Data FactoryAzure DatabricksPySparkGitHub Actions

Key outcomes:

  • Developed robust integration pipelines on Azure Data Factory for smooth data flow.

Merchandizing Data Migration – Data Engineer

Overview: This project implemented a merchandising solution for a retail company, focusing on migrating data from Hadoop to Google Cloud Platform (GCP) using Hive-to-BigQuery conversion. Responsibilities: Demonstrated expertise in migrating data from Hadoop to Google Cloud Platform (GCP) for a merchandising solution.

HadoopGCPBigQueryAirflow

Key outcomes:

  • Successfully migrated merchandising data from Hadoop to Google Cloud Platform (GCP).

Business Intelligence Solution Implementation – Data Engineer

Overview: This project centered on implementing a Business Intelligence (BI) solution for a retail company, focusing on migrating data from SQL Server to Google Cloud Platform (GCP) using BigQuery. Responsibilities: Implemented a Business Intelligence solution with a focus on migrating data from SQL Server to Google Cloud Platform (GCP) using BigQuery.

SQL ServerGCPBigQueryPython

Key outcomes:

  • Implemented a Business Intelligence solution focused on data migration from SQL Server to GCP using BigQuery.

5+ years of industry experience

HealthTechReported in resume
Logistics & Supply ChainReported in resume

Ready to work with Pallavi?

Onboard within 48 hours. No long hiring cycles, no recruiter middleman.

At a Glance

LocationBengaluru
Experience5+ years
Work moderemote
Direct hirePossible
Start within48 hours
From$1,868/ month

Single contract. Billed in USD.

Typically responds within 4 business hours.

5-day replacement guarantee
48-hour onboarding, single invoice
Direct chat — no recruiter middleman

Top Skills

Python
9/10
SQL
9/10
Snowflake
9/10
Airflow
9/10
DBT
9/10
Seniority signals
Owns production deploysSystem owner
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Technical skills assessed & verified
Background & identity checked
English communication verified
Ready to onboard in 48 hours

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Pallavi

Data Engineer