Yakeey is a fast‑growing PropTech company headquartered in Casablanca, Morocco.  Our mission is to simplify and accelerate real‑estate transactions by connecting buyers, sellers, renters and agents through a single digital platform.  We operate a multi‑product portfolio—including a property marketplace, a credit application and processing platform and a valuation tool—powered by a modern data architecture that underpins analytics, reporting and AI‑driven services.

As Lead Data Engineer, you will own the strategic direction and day-to-day excellence of our data platform. You will lead a team of engineers, drive architectural decisions, and ensure a reliable, high-performance data stack that empowers product and operations teams with actionable insights.

Key Responsibilities

• Maintain and optimize our data platform (RDS, Redshift, S3), ensuring high availability, performance and cost efficiency to support analytics and operations.

• Develop and manage ELT pipelines with Airbyte to ingest data from diverse sources and keep the data warehouse and data lake up to date.

• Model and transform data using dbt to deliver clean, well‑structured datasets and meaningful KPIs for product and operations teams.

• Orchestrate data workflows with Prefect, automating tasks such as data ingestion, transformation and quality checks.

• Collaborate with product, operations and analytics teams to understand data needs, define metrics and build data products that support decision‑making.

• Implement and enforce data governance practices, including monitoring, testing and documentation, to ensure data accuracy and trustworthiness.

• Proactively monitor pipeline performance and resolve issues, continuously improving reliability and scalability.

• Stay current with emerging tools and best practices in data engineering to enhance the stack and support advanced use cases like MCP‑based agents and RAG architectures.

• Curiosity for next‑generation AI technologies – Demonstrated interest in or experience with intelligent agents, large language models (LLMs), Model Context Protocol (MCP) and retrieval‑augmented generation (RAG) architectures.  A “geek” mindset that enjoys exploring and experimenting with emerging AI tools and applying them in practical scenarios.

• 5 to 8 years of experience in data engineering with at least 1–2 years in a lead or senior role and hands‑on work in SQL, data warehousing and cloud platforms.

• Strong proficiency with relational databases (Postgres) and columnar warehouses such as Redshift; familiarity with object storage (S3) and AWS services.

• Experience building and maintaining data ingestion pipelines using Airbyte or similar ELT frameworks.

• Proficiency in dbt for data transformation and modelling.

• Experience orchestrating workflows using Prefect or equivalent tools.

• Programming skills in Python and/or Java.

• Understanding of data governance, testing and CI/CD for data pipelines.

• Excellent problem‑solving skills and ability to work collaboratively across technical and business teams.

• Experience in fintech, proptech or other regulated domains is an advantage; proficiency in French or Arabic is a plus.

The recruitment process at Yakeey:

• A first conversation with the HR team to get to know you better and introduce you to our project

• A test or a practical case study related to the position

• A role-specific interview with your future manager

• A final meeting with top management (if needed)

If everything is approved: we send you an offer, and off we go!

🎉 On your first day, the HR team will welcome you and immerse you in the Yakeey universe: our mission, our challenges, and our tools. Then you’ll join your team for a tailored onboarding experience.

Why Join Yakeey?

At Yakeey, data isn’t just a support function—it’s a strategic lever. You’ll shape how data informs every decision across the company, from product evolution to credit approval workflows. If you want to build the foundations of a data-driven organization in a fast-paced, high-impact environment, we’d love to hear from you.