Data Engineer

🗓️ Working Days and Hours: Monday to Friday, 9 AM – 6 PM (UK Hours); Potential for Flexible Hours

📍 Location: Remote/Online

💷 Salary Range: Attractive, Top-of-Market Salary (paid in GBP/USD)

Palm Outsourcing helps international companies find talent in Egypt.

Please note, we will only be considering excellent applicants with solid demonstrable experience. If you do not have clear and evidenced experience, you will be immediately rejected, so please do not apply.

Contrastingly if you feel you are a right fit relative to the requirements below, please proceed.

Opportunity Overview

Our client is building data and AI-driven systems where clean pipelines, strong data modelling, and production-ready delivery matter. This role presents a strong opportunity to own the foundations: ingestion, enrichment, and transformation pipelines that power analytics and AI/LLM workflows, enabling faster and higher-confidence decision-making.

Role Description

We're looking for a Data Engineer to join our client's team. If you're a hands-on engineer who enjoys end-to-end ownership—building pipelines, improving data reliability, and supporting AI-ready datasets—this could be the opportunity for you.

You'll play a crucial role in designing and maintaining scalable data pipelines, integrating APIs and third-party data sources, improving data quality and performance, and partnering with stakeholders to ship reliable data products. Where applicable, you will also support AI/LLM workflows (e.g., data preparation for RAG, embeddings, and semantic search).

Key Responsibilities

• Data pipeline development – Design, build, and maintain reliable ingestion and transformation pipelines.
• Data enrichment & automation – Integrate APIs and automate data ingestion, enrichment, and scheduling.
• ETL/ELT best practices – Implement repeatable workflows with clear validation, monitoring, and documentation.
• Data modelling – Contribute to schema design and modelling for analytics and downstream products.
• Performance optimisation – Improve query performance, pipeline efficiency, and runtime reliability.
• Data quality & observability – Implement checks, alerting, and monitoring to prevent silent failures.
• Stakeholder collaboration – Work closely with analysts and engineers to translate needs into shippable data outputs.
• AI/LLM readiness – Support datasets and retrieval layers used for embeddings, vector search, and LLM-backed features.

Minimum Qualifications

• Strong SQL and Python skills with proven experience delivering production data workflows.
• Experience building data pipelines (batch and/or near-real-time) across multiple sources.
• Understanding of data modelling fundamentals (normalisation, dimensional modelling, trade-offs).
• Experience working with cloud data storage and compute (Azure or AWS or GCP).
• Strong attention to detail; able to work independently and reliably under pressure.