Who are we
There are 2B adults worldwide that don’t have a bank account. 2B. That’s ~40% of the world’s adult population. 350M of these live in Sub Saharan Africa. They are hardworking, young, connected adults that are invisible to the traditional banking system. Fido is changing that. We are building a borderless digital bank so that everyone can access financial products like credit, savings, and payments that make lives easier and better.
Are you tired of building boring enterprise software? Want to be an early employee in a unique consumer brand? Want to do work that has an impact on society? Join us. We build consumer products that are powered by a magical cocktail of real time mission critical ML models, behavioral psychology and financial engineering. We promote meritocracy, decide fast and commit, and worship data. Come join us as one of our early team members.
Join our mission to make financial services accessible and improve the lives of millions of people in Africa and emerging markets.
What you will do
- Manage data pipelines and ETLs that collect and transform data to support ML models, analysis, and reporting
- Working in a high volume production environment that gets bigger and bigger
- Make data standardized and reusable, from architecture to production
- Working with a number of off-the-shelf tools including Spark, Airflow, Kafka, DynamoDb, SQS, S3, RedShift, Mysql, but often push them past their limits
Who you are
- At least 3+ years of experience in data engineering in the big data domain
- At least 3+ years of coding experience with at least one of the following: Java, Python.
- Experience building and optimizing data pipelines, architecture, and data sets
- Familiarity with data engineering tech stack - ETL tools, Spark, Kafka
- SQL expertise, working with various databases (relational and NoSQL), data warehouses, and 3rd party data sources and AWS cloud services
- End to end experience - owning feature from an idea stage, through design, architecture, coding, integration and deployment stages
- Cloud - AWS, Azure, Google Cloud - an advantage
- A B.Sc. in industrial/information systems engineering, computer science, statistics, or equivalent