There are billions of people in the world that are creditworthy; Juvo provides a way for every one of them, regardless of their income and geographical location, to gain access to financial services  via their mobile phones. Juvo uses data science, machine learning, and game mechanics to create financial identities for anonymous and understanding prepaid mobile subscribers across the globe, providing ongoing personalized access to to otherwise unattainable financial services.

In our first 3 years, we have deployed in 25 countries across four continents and have a reach of 500 million mobile subscribers. Juvo is a team of passionate people with a deep understanding of the digital consumer, data science, global telecom business, and emerging financial services. Together, we believe that we can make the world a better place.

About the Job

Juvo is looking for a Data Engineer to be a driving force in the design and development of data solutions on our AWS hosted platform. Not only will you belong to a  high performing team of engineers and scientists, you’ll also interact with and inform Juvo’s internal stakeholders if technological developments that go into a scalable financial platform meant to serve billions of people in the underbanked world. Data Engineering is instrumental in abstracting, modularizing and stress-testing our Data Science stack, allowing us to operationalize data science work across 4 continents and 50 countries, touching 500M end users over the next two years.

At Juvo, you’ll be responsible for turning one of the World’s most interesting and valuable data sets into financial identities at the core of the global financial platform we’re building to trigger fair, sustainable economic growth.


  • Contribute to the design and implementation of scalable ETL and data processing systems to go into our big data ecosystem including data collection, cleaning, processing, ETL and the creation of a common data lake.
  • Work with engineering and infrastructure architects to improve data strategy, quality and governance.
  • Work closely with both business and partner stakeholders to quickly deliver high-quality applications.
  • Collaborate with architects, product owners, data scientists and test engineers to help bring data science R&D projects into Production.
  • Build and scale Internal Analytics, Reporting, and Decisioning platform on top of a common data lake.
  • Manage data infrastructure to grow and support the Data Science and Engineering team in relation to the construction of performant data products.
  • Establish the technical direction for the team, driving the necessary changes and making appropriate technology choices working collaboratively with the Data Science, Product and Engineering Teams.
  • Maintain and scale production environments for ML-based data products.


  • BS/MS/PhD in Computer Science or related quantitative fields.
  • 2+ years experience in enterprise-scale software architecture is preferred
  • Atleast 3 years of experience in data engineering and software development.
  • 2+ years of experience designing data warehouse/data lake and ETL architectures with big data technologies such as Spark, Spark Streaming, Hive, Storm, Sqoop, Kafka, Hbase, and HDFS.
  • 2+ years of experience with AWS services.
  • Experience with SQL/NoSQL systems such as MongoDB, Cassandra, Solr, Elasticsearch, Redshift, DynamoDB, etc.
  • Fluent in at least one of the following programming languages Scala, Python, Java.
  • Familiar with infrastructure frameworks such as Terraform, Docker, Kubernetes, etc.
  • Experience in Agile processes and scrum.
  • Highly organized, structured work approach and dependable.

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