Find Proven, Expert Data Engineers

Here's the best kept secret for
finding data engineers.

Demand for AI, ML, Analytics & Data Engineers is 5X the supply

How will you find quality data engineers to run your data projects? 

Build a World-Class Data Team In Just a Few Days

Learn How Your Growing Company Can Build and Retain Proven Data Engineers In a Fast and Cost-Effective Way.

  • Stop competing with Silicon Valley giants for engineers
  • The savvy ways companies are solving for talent challenges
  • Hire the top 1-3% rigorously vetted engineers in the world
  • Tap into talented, continuously up-skilled data engineers
  • Get your data and AI projects back on tack

The Right Skills. The Right Roles.

Machine Learning Engineering

Data Engineering

Data Analytics Engineering

Data Analysis & Visualization

  • Role:  Define and deploy AI models; ensure their usefulness in production.  
  • Top Tools & Skills:  Swift, Go, Python, TensorFlow, Pytorch, Recurrent, Convolutional and Attention Architectures, NLP, Computer Vision, Time Series Forecasting.

Role:  Manage the entire data lifecycle from various sources and prepare the data for the team when AI models are deployed. 

Top Tools & Skills:  SQL, Spark, Hive, Airflow, MongoDB, Cassandra, Hadoop, and various AWS services (Glue, Redshift, EMR, DynamoDB)

  • Role:  Provide clean, tested and documented data sets and data models to end-users across the entire organization. 
  • Top Tools & Skills:  Snowflake, Airbyte, dbt, SQL, Perfect, Python, Looker, Hex.
  • Role:  Analyze data trends; identify key data insights; ensure business value is delivered by AI projects.  
  • Top Tools & Skills:  Pandas, Scikit-learn, Spark, Tableau, Cube.js, AWS Quicksight, AWS Redshift