Data Engineer

Job Summary

We are seeking a Senior / Lead Data Engineer to design, build, and scale AI-powered, cloud-native data platforms that support enterprise analytics, machine learning, and business-critical decision-making.

The ideal candidate will bring deep expertise in data engineering, cloud data warehouses, cost optimization, and AI-assisted development , with a proven track record of delivering high-impact, revenue-generating data platforms and intelligent automation solutions at scale.

Key Responsibilities

Data Platform & Pipeline Engineering

• Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, dbt, and modern orchestration tools.
• Build and optimize cloud-based data warehouses (BigQuery or equivalent) supporting high-volume analytical workloads.
• Implement robust data modeling (dimensional and analytical models) to enable self-service analytics and AI use cases.
• Ensure data quality, integrity, and freshness through automated validation frameworks and monitoring.

AI-Driven Automation & Innovation

• Design and deploy AI-powered internal tools and agents to automate data engineering workflows, incident diagnosis, and root cause analysis.
• Integrate AI agents with collaboration tools (e.g., Slack) to improve operational efficiency and reduce incident resolution time.
• Apply AI-assisted development techniques to accelerate delivery, improve code quality, and reduce manual effort across teams.

Performance & Cost Optimization

• Lead cloud cost optimization initiatives , including query optimization, architectural redesign, and usage monitoring.
• Drive measurable reductions in data platform operational costs while maintaining performance and reliability.

Cloud & DevOps

• Build and deploy data services using containerized and CI/CD-driven workflows .
• Collaborate with DevOps and platform teams to ensure scalable, secure, and reliable cloud infrastructure.
• Support multi-cloud or hybrid environments as required (GCP, Azure).

Leadership & Collaboration

• Provide technical leadership and mentorship to data engineers.
• Establish SOPs, best practices, and engineering standards across the data function.
• Partner closely with product, analytics, and business stakeholders to translate requirements into scalable data solutions.

Required Skills & Qualifications

Technical Skills

• Programming: Python (expert), SQL (expert), Shell scripting (advanced).
• Data Engineering: dbt, ETL/ELT pipelines, data warehousing, data modeling, data quality frameworks.
• Cloud Platforms: Google Cloud Platform (BigQuery, Cloud Run) – strong experience; Azure familiarity is a plus.
• Orchestration & Automation: Airflow or equivalent.
• DevOps & Tooling: Git, Docker, CI/CD pipelines.
• AI & ML Exposure: AI agent frameworks, ML pipelines, model lifecycle management, observability tools.

Data Management

• Cost optimization and performance tuning.
• Data governance, cataloging, and best-practice documentation.

Education

• Bachelor’s degree in Computer Science or related field.
• Master’s or Postgraduate qualification in Data Science is preferred.

Nice to Have

• Experience delivering AI/ML pipelines in production environments.
• Exposure to government, public sector, or regulated enterprise data platforms .
• Experience building observability and monitoring tools for data platforms.
• Prior work on Arabic-language or regional datasets .