Krishna  ·  Python / GenAI Data Engineer  ·  4+ yrs

Mid-Level
4+ years experienceremote
Available within 48 hrs

Proof of scale

240 projects migrated
carbon-neutral goal by 2035
240 projects migratedcarbon-neutral goal by 2035
Built for
Nestle

About Krishna

Krishna is a Senior Data Engineer with 4+ years of experience in data and software engineering, specializing in Gen AI tool development and LLM integration. He has successfully led a team of 12 Data Engineers and executed large-scale migrations.

4+ years of commercial experience in

FinTechAI / ML PlatformLegal TechManufacturing & Industrial

Skills(23)

AzureFlaskGPT-3.5Node.jsPythonSQLSnowflakedbtGitLab CIGPT-4TableauTalendMonte CarloCollibraDatabricksAzure Data FactorySparkSQLLogic AppsAzure SQLSAP BWSAP HANAADLSPySpark

Why hire Krishna?

Production deploy authorityMentored 12 juniorsLed large-scale migrations

Led a team of 12 Data Engineers to build Gen AI tools.

Successfully migrated 240 projects from a commercial DataOps platform to an in-house GitLab + DBT platform.

Developed ETL pipelines and a data lake for Nestle, supporting their carbon-neutral goal by 2035.

Implemented fault-tolerant solutions for startups and MNCs using Data, Python, and Cloud.

Successfully migrated approximately 240 projects from DataOps.live to an in-house platform.

Built an AI/LLM-powered tool for Anti-Money Laundering (AML) policy checks, utilizing GPT-3.5 and GPT-4.

Developed a central data catalog with data quality metrics and Row Level Security.

Project highlights(5)

Anti-Money Laundering Policy Check – LLM Developer

Overview: Developed a tool to automate AML policy checks for clients, simplifying manual processes. Responsibilities: Built the core tool, processing policy documents and generating compliance reports. Designed and implemented a RAG pipeline to handle large volumes of documents. Utilized GPT-3.5 and GPT-4 Azure Deployments hosted in the EU, ensuring GDPR compliance.

PythonFlaskGPT-3.5GPT-4Azure

Key outcomes:

  • Simplified manual AML policy checks for clients.

  • Implemented a RAG pipeline for processing extensive policy documents.

Finance Data Products – Snowflake Developer

Overview: Built finance data products in Snowflake, integrating data from SAP cubes and static files. Responsibilities: Developed data products as a Snowflake Developer. Utilized DataOps.live (DBT) for building and managing data products. Integrated data from SAP cubes via Talend jobs and various seed files.

SnowflakeDBTSQLPythonTableauTalend

Key outcomes:

  • Built robust finance data products in Snowflake.

  • Supported business users with data queries and ad-hoc changes.

DataOps.live to Inhouse Data Platform Migration – Snowflake Developer

Overview: Migrated approximately 240 projects from a commercial DataOps.live platform to an in-house GitLab + DBT platform. Responsibilities: Led the migration of 240 projects from DataOps.live to an in-house platform as a Snowflake Developer. Collaborated with project-specific tech leads to understand migration scope and requirements.

DBTSnowflakeSQLGitLab CIMonte CarloCollibra

Key outcomes:

  • Successfully migrated ~240 projects from DataOps.live to an in-house platform.

  • Standardized code structure and configured data governance tools.

Nestle Packaging Analytics Project – Databricks Developer

Overview: Developed ETL pipelines and a data lake to support a PowerBI dashboard for business users, contributing to Nestle's carbon-neutral goal by 2035. Responsibilities: Worked as a Databricks Developer, building ETL pipelines. Implemented pipelines in Azure Data Factory and Databricks Notebooks.

AzureDatabricksAzure Data FactorySparkSQLLogic AppsAzure SQLSAP BWSAP HANAADLSPythonPySpark

Key outcomes:

  • Developed ETL pipelines and a data lake to support a PowerBI dashboard.

  • Contributed to Nestle's carbon-neutral goal by 2035.

Central Data Catalogue Project – Azure Data Engineer

Overview: Built a central data catalog for the entire organization's data, enhancing discoverability and governance. Responsibilities: Worked as an Azure Data Engineer to build the data catalog. Developed Python/SQL scripts to fetch metadata from various data sources.

Azure Data FactoryDatabricksSQLNode.jsPython

Key outcomes:

  • Built a central data catalog for organization-wide data.

  • Implemented data quality metrics and Row Level Security.

Industry experience

FinTech

Reported in resume

AI / ML Platform

1 project
  • •Anti-Money Laundering Policy Check— LLM DeveloperPython · Flask · GPT-3.5 · GPT-4 +1

Legal Tech

1 project
  • •Anti-Money Laundering Policy Check— LLM DeveloperPython · Flask · GPT-3.5 · GPT-4 +1

Manufacturing & Industrial

3 projects
  • •Anti-Money Laundering Policy Check— LLM DeveloperPython · Flask · GPT-3.5 · GPT-4 +1
  • •Nestle Packaging Analytics Project— Databricks DeveloperAzure · Databricks · Azure Data Factory · SparkSQL +7
  • •Central Data Catalogue Project— Azure Data EngineerAzure Data Factory · Databricks · SQL · Node.js +1

Ready to work with Krishna?

Schedule an interview and onboard within 48 hours. No long hiring cycles.

At a Glance

Experience4+ years
Work moderemote
Starting from₹1.8 L/mo
Direct hirePossible
Start within48 hours
From₹1.8 L/ month

Single contract. No agency markup confusion.

Typically responds within 4 business hours.

5-day replacement guarantee
48-hour onboarding, single invoice
Direct chat — no recruiter middleman
Seniority signals
Owns production deploysGreenfield architectSystem ownerCode reviewerMentor / leads juniors
VerifiedVetted by Witarist
Technical skills assessed & verified
Background & identity checked
English communication verified
Ready to onboard in 48 hours

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Krishna

GEN AI