Data Engineer Needed at Flutterwave
Flutterwave was founded on the principle that every African must be able to participate and thrive in the global economy. To achieve this objective, we have built a trusted payment infrastructure that allows consumers and businesses (African and International) make and receive payments in a convenient borderless manner.
To make it easier for Africans to build global businesses that can make and accept any payment, anywhere from across Africa and around the world.
Simplifying payments for endless possibilities.
The role: Are you an avid learner, constantly looking to improve and innovate? We are seeking a highly skilled and experienced Data Engineer to partner with in driving our data strategy. You’ll play a key role in driving our journey towards becoming a fully data-driven organization and embedding a data-first culture across the business.
Principal Duties and Responsibilities
- Design and build high-performance, secure, and scalable data pipelines to support data science projects following software engineering best practices.
- Curate, wrangle, prepare data, and feature engineering to be used in machine learning models
- Design and develop the data and analytics platform selecting the right technologies for each problem at hand (big-data stack, SQL, no-SQL, etc.)
- Build a modular pipeline to construct features and modeling tables.
- Build a sense of trust and rapport that creates a comfortable & effective workplace and experience in working as part of an agile squad
- Work with Data Analytics and Science team to understand the business needs and build impactful analytics solutions.
- Coordinate and collaborate with the Data Analytics team & other engineering teams to align on our roadmap
Competency and Skill Requirement
- 4+ years’ experience in a data role (Data Engineer, Data Analyst, Analytics Engineer, etc.)
- 2+ years of hands-on experience building data pipelines in production and the ability to work across structured, semi-structured, and unstructured data.
- Hands-on experience implementing ETL (or ELT) best practices at scale .2+ years of experience in ML pipeline for streaming/batch workflow.
- Hands-on knowledge and experience in working with the modern data stack (Snowflake, BigQuery, Redshift, dbt)
- Hands-on knowledge and experience with orchestration tools (Airflow, Prefect, or Dagster)
- Professional experience using Python for data processing, SQL, Git (as source code versioning and CI/CD), and Apache Kafka.
- Natural ability to manage multiple initiatives and clients
- Authorization to work in the country without sponsorship
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