Data Engineer - DWH

FairMoney is a pioneering mobile banking institution specializing in extending credit to emerging markets. Established in 2017, the company currently operates primarily within Nigeria, and it has secured nearly €50 million in funding from renowned global investors, including Tiger Global, DST, and Flourish Ventures. 

In alignment with its vision, FairMoney is actively constructing the foremost mobile banking platform and point-of-sale (POS) solution tailored for emerging markets. The journey began with the introduction of a digital microcredit application exclusively available on Android and iOS devices. Today, FairMoney has significantly expanded its range of services, encompassing a comprehensive suite of financial products, such as current accounts, savings accounts, debit cards, and state-of-the-art POS solutions designed to meet the needs of both merchants and agents.FairMoney thrives on its diverse workforce, bringing together talent from over 27 nationalities. This multicultural team drives the company’s mission of reshaping financial services for underserved communities.To gain deeper insights into FairMoney’s pivotal role in reshaping Africa’s financial landscape, we invite you to watch informative video.

Role and Responsibilities

• Design and maintain batch and/or streaming data pipelines from raw ingestion to warehouse-ready tables
• Build and manage staging, source, and transformation layers in the data warehouse
• Implement incremental loading strategies for large datasets
• Handle append-only data, late-arriving events, and change data capture scenarios
• Write efficient SQL transformations and merge/upsert logic
• Design and maintain fact tables, dimension tables, and snapshot tables
• Ensure data quality through validation checks, monitoring, and reconciliation
• Support schema evolution and backward-compatible changes
• Optimize pipeline performance, cost, and reliability
• Work closely with analytics, product, finance, and engineering teams to ensure accurate and usable data
• Document pipelines, data models, and data contracts
• Participate in debugging data issues and improving pipeline observability

Technical Requirements

• Strong SQL skills (joins, window functions, aggregations, incremental logic, performance tuning)
• Experience building data pipelines using Python or similar scripting language
• Experience with at least one modern data warehouse (BigQuery, Snowflake, Redshift, etc.)
• Familiarity with orchestration tools (Airflow/Composer or similar)
• Understanding of incremental pipelines, partitioning, and idempotent processing
• Experience designing and maintaining data models for analytics
• Understanding of deduplication, late data handling, and merge strategies
• Familiarity with version control (Git) and collaborative development workflows

Preferred (Good-to-Have)

• Experience with dbt or similar transformation frameworks
• Exposure to streaming systems (Kafka, Kinesis, etc.)
• Experience migrating or refactoring pipelines
• Experience implementing data quality frameworks or monitoring
• Familiarity with Shell Scripting, CI/CD for data pipelines
• Experience working in a fintech, lending, or transactional data environment

Requirements

• 2–5 years of experience working with production data pipelines and warehouse systems, with demonstrated ability to:
• Collaborate effectively with analytics and product teams
• design core warehouse tables
• debug data issues independently
• support evolving data needs of a growing organization
• Values correctness over shortcuts
• Understands trade-offs between batch vs incremental vs streaming
• Writes clear, maintainable SQL and pipeline logic
• Tests and validates before releasing changes
• Takes ownership of data quality and reliability
• Continuously improves pipeline design and observability
  
  

Benefits

• Training & Development
• Family Leave (Maternity, Paternity)
• Paid Time Off (Vacation, Sick & Public Holidays)

Recruitment Process

• A screening interview with one of the members of the Talent Acquisition team ~30 minutes.
• Assignment to be done at home.
• Technical Interview - SQL/Python proficiency with Tech.Team ~60 minutes
• Technical design interview - Shubham Jain ~60 minutes