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Flutterwave is seeking an Analytics Engineer to own the transformation layer that converts raw, streaming, and batch data into clean, tested, and well-documented datasets. You will build ingestion pipelines using Estuary, model data with dbt, and write performant SQL and Python on Amazon Redshift to deliver accurate, fast, and self-serve analytics.
Key responsibilities include:
• dbt Modeling: Build and maintain modular, tested, documented dbt models progressing from staging through intermediate to marts; manage tests, macros, and materializations.
• Estuary Pipelines: Construct and monitor real-time and batch ingestion workflows, including change data capture (CDC) from operational sources; handle schema evolution, backfills, and connector troubleshooting.
• Redshift & SQL: Write performant SQL, design dimensional models, and optimize warehouse performance through distribution keys, sort keys, workload management, and cost optimization.
• Python Automation: Automate data transformations, orchestration hooks, custom dbt macros, and API integrations.
• Data Quality & Testing: Establish comprehensive tests, freshness checks, monitoring, and alerting; own CI/CD for analytics code via Git.
• Documentation & Semantics: Maintain model and metric documentation with a consistent semantic layer to ensure single-sourced definitions.
• Cross-functional Collaboration: Partner with analysts, data scientists, and business teams to translate requirements into scalable, trustworthy datasets.
• Governance: Apply access controls, PII handling, and data privacy practices aligned with GDPR and SOC 2 standards.
Required qualifications: 3+ years in analytics engineering, data engineering, or similar role; strong production SQL with window functions and CTEs; hands-on dbt experience in production; Python proficiency for data workflows; Amazon Redshift expertise; experience with ELT/CDC tools (Estuary, Fivetran, Airbyte, or Debezium); solid Kimball dimensional modeling and star schema knowledge; Git-based version control comfort.
