Mid/Senior Data Engineer

Yassir is the leading super App in the Maghreb region set to changing the way daily services are provided. It currently operates in 45 cities across Algeria, Morocco and Tunisia with recent expansions into France, Canada and Sub-Saharan Africa. It is backed (~$200M in funding) by VCs from Silicon Valley, Europe and other parts of the world. We offer on-demand services such as ride-hailing and last-mile delivery. Building on this infrastructure, we are now introducing financial services to help our users pay, save and borrow digitally. Helping usher the continent into a digital economy era. We’re not just about serving people - we’re about creating a marketplace to bring people what they need while infusing social values.

Responsibilities

Build a centralized data lake on GCP data services by integrating diverse data sources throughout the enterprise.

Develop, maintain, and optimize Spark-powered batch and streaming data processing pipelines. Leverage GCP data services for complex data engineering tasks and ensure smooth integration with other platform components.

Design and implement data validation and quality checks to ensure accuracy, completeness and consistency across our data workflows.

Work closely with the AI / ML team to enable AI use cases and in particular address data needs for Machine Learning model development and monitoring.

Collaborate with cross-functional teams, including Data Analysts and other business users from Operations, Marketing and Commercial departments, to extract valuable insights and enable data-driven decision making.

Collaborate with the Product teams to design, implement, and maintain the data models for analytical use cases.

Engage in technology exploration and research, the development of PoC’s, conducting deep investigations.

Design and manage ETL/ELT processes, ensuring data integrity, availability, and performance.

Troubleshoot data issues and conduct root cause analysis when reporting data is in question.

Work on Gen AI related initiatives aligned with the company goals.

Required Technical Skills

• PySpark - Batch and Streaming
• GCP - Dataproc, Dataflow, DataStream, Dataplex, Pub/Sub, BigQuery and Cloud Storage
• NoSQL (preferably MongoDB)
• Programming languages: Scala/Python
• Great Expectation, or similar DQ framework
• Familiarity with workflow management tools like: Airflow, Prefect or Luigi
• Understanding of Data Governance, Data Warehousing and Data Modelling
• Good SQL knowledge

Business

• Able to communicate effectively, distill technical knowledge into digestible messages in a succinct / visual way
• Proactively identify and contribute with team development initiatives, and supporting junior members
• Good to have skills
• Infrastructure-as-Code, preferably Terraform

Docker and Kubernetes

Looker

• AI / ML engineering knowledge
• Lineage, or relevant tools e.g. Atlan

DBT