We are looking for a data engineering manager in our Product Engineering team who will help us
to develop data solutions to discover the information hidden in vast amounts of data and help us
make smarter decisions to deliver even better products. Your primary focus will be on applying
Data Engineering Skills to create and improve Aurigo’s Data Infrastructure for solving business
problems. The ideal candidate must have a proven ability to drive business results by building
powerful data platforms and apps. You must be comfortable working with a wide range of
stakeholders and functional teams. The right candidate will have a passion for discovering
solutions hidden in large data sets and working with stakeholders to improve business outcomes.
This role also gives you the opportunity to create and mentor a complete data science team.
Desired Skills and Experience:
• Specific Experience: 5-7 years of experience with 1 - 2 years in a dedicated data science
• Experience with a wide range of learning/statistical techniques such as automated
scoring or recommendation systems, but also some practical familiarity with modern
techniques such as Ensemble Methods, Deep Learning, or Reinforcement Learning.
• Assembling large, complex sets of data that meet non-functional and functional
• Building required infrastructure for optimal extraction, transformation and loading of
data from various data sources using AWS and SQL technologies
• Building analytical tools to utilize the data pipeline, providing actionable insight into key
business performance metrics including operational efficiency and customer acquisition
• Working with stakeholders including data, design, product, and executive teams and
assisting them with data-related technical issues
• Strong implementation experience with high-level languages, such as Python, PySpark
• Leadership: At least 1 years of experience in leading a team. The candidate needs to
have entrepreneurial instincts, strong technical and communication skills, flexibility, and
the ability to build the team around him/her to scale.
• Spark & SQL (Must)
• Python (Programming Language)
• Pandas, Numpy, ScikIt Learn, Tensor flow and Keras
• ETL tools (AWS Glue, Azure Data Factory anyone)
• NO SQL Database (DynamoDB, Mongo DB etc.)
• Kafka or any other event streaming