About the job

SummaryBy Outscal

Data Engineer with 3+ years of experience, proficient in Python, SQL, ELT pipelines and AWS, to design and build data infrastructure for healthcare AI platform.

Description

VI is the market leading Enterprise-AI platform for health, serving the world’s largest health organizations — from Fortune 500 health providers to pharma and consumer brands — helping them maximize acquisition, enrollment, engagement, retention, and health outcomes. Vi offers 3 main product lines: Acquire, Engage and Transform.


Backed by $60M+ in R&D, our powerful platform serves over 100 million members daily — and growing. We are based in New York, Austin, Nashville & Tel Aviv.


We are looking for a talented DATA ENGINEER to join our growing Engineering group.

As a Data Engineer at Vi you will work closely with all R&D teams and business stakeholders to own the entire data process and shape our data strategy.

This is a great opportunity for someone who is passionate about cloud data infrastructure / technologies and wants to make a significant impact in a fast-paced startup environment.

Responsibilities

  • Design, develop and implement robust data pipelines using ETL/ELT to move data from various sources into our lakehouse while ensuring scalability, security, and performance
  • Ensure quality and integrity of data by implementing validations, testing and monitoring
  • End-to-end feature development and ownership, from design to production
  • Work directly with stakeholders to develop a solid understanding of the business application and requirements for which the application is being designed

Requirements

  • BSC in a related technical field or equivalent practical experience
  • Over 3 years of experience in a Data Engineering role
  • Coding experience with Python
  • Experience with SQL and NoSQL databases 
  • Experience with data modeling, and building ELT/ETL pipelines
  • Experience with common data warehouse and lakehouse technologies
  • Experience with AWS platform
  • Experience working with Git, CI-CD flows and Docker
  • Experience building data pipelines with big data frameworks such as Spark
  • Technologically diverse background and ability/willingness to learn new things quickly

Advantages

  • Experience working closely with data scientists / data science project (MLOps)
  • Experience with big data architectures and infrastructures
  • Experience with BI tools (Tableau, Looker, power bi etc.)
  • Experience with IaC technologies like CDK & CloudFormation

Why choose Vi?

At Vi we provide you with the autonomy to deliver, the safety to make mistakes and the opportunity to help millions of people live happier and healthier lives. 


We believe that building a great product and a great company starts with finding amazing people and helping them grow and develop professionally and personally. At Vi, you’ll be surrounded by curious, witty, and passionate people that are hungry to drive real impact.


But if that’s not enough, we also offer a competitive salary, stock plans, & loads of extra perks

About The Company

Vodafone Idea Limited is an Aditya Birla Group and Vodafone Group partnership. It is India’s leading telecom service provider. The Company provides pan India Voice and Data services across 2G, 3G and 4G platform. With the large spectrum portfolio to support the growing demand for data and voice, the company is committed to deliver delightful customer experiences and contribute towards creating a truly ‘Digital India’ by enabling millions of citizens to connect and build a better tomorrow. The Company is developing infrastructure to introduce newer and smarter technologies, making both retail and enterprise customers future ready with innovative offerings, conveniently accessible through an ecosystem of digital channels as well as extensive on-ground presence. The Company is listed on National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) in India.

Tel Aviv District, Israel (On-Site)

Worldwide (Remote)

Tel Aviv District, Israel (On-Site)

Tel Aviv District, Israel (On-Site)

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