Head of Data Engineering

Overview

This opportunity is shared on behalf of a partner organization that will handle applications and the remaining recruitment stages. The hiring company is seeking a Head of Data Engineering in Saudi Arabia.

The position is a chance to guide the growth of a large-scale data platform inside a fast-moving technology business.

You will set the architecture, engineering practices, and long-term technical direction that support reporting, analytics, and data-led decision-making.

In this leadership role, you will combine strategic oversight with practical engineering to create robust platforms, improve trust in data, and unlock advanced analytics and machine learning use cases.

You will work closely with teams across the business to turn complex needs into scalable technical solutions.

The role is suited to someone who can balance hands-on technical depth, people leadership, and a long-range view of how data infrastructure should evolve.

You will also have freedom to influence technology decisions and help define best practices in a remote-first working setup.

Key Accountabilities

• Shape, implement, and continually refine a data architecture that can support rapid international expansion.
• Set standards for data engineering, including CI/CD workflows, automation, code versioning, and strong operational discipline.
• Maintain high levels of reliability, security, governance, and performance across systems used for analytics and machine learning.
• Make key technology choices around cloud platforms, tooling, and data engineering solutions.
• Lead, coach, and grow a high-performing data engineering team, encouraging ownership, teamwork, and ongoing improvement.
• Direct the creation of efficient ETL and ELT processes and modern data pipelines.
• Work with business, product, analytics, and technical stakeholders to convert complex requirements into scalable solutions.
• Create operating processes that improve data quality, accessibility, and the overall effectiveness of the data function.

Requirements

• Strong background in leading data engineering within a high-growth, scale-up, or technology-focused environment.
• At least 3 years of experience managing and developing engineering teams, with the ability to mentor and motivate technical professionals.
• At least 5 years of hands-on experience using programming languages such as Python, Java, or Scala to build data systems.
• Deep understanding of data architecture, data warehousing, big data platforms, and cloud infrastructure.
• Solid experience handling relational and NoSQL databases at scale.
• Strong command of Google Cloud Platform (GCP) and modern cloud-native data solutions.
• Proven ability to design data pipelines that are secure, dependable, and high performing.
• Ability to provide strong technical direction and drive engineering ownership and excellence.
• Excellent communication and collaboration skills for working across multiple teams.
• Advanced qualifications in Computer Science, Engineering, or a related field are an added advantage.

Perks and Benefits

• Remote-first arrangement with flexibility to work from anywhere in the world.
• Chance to influence the technical strategy and data foundation of a global technology business.
• Work-life balance culture intended to support sustainable performance and innovation.
• High-impact leadership position with ownership of critical data systems and engineering practices.
• Exposure to international teams and products used at a global scale.

Additional Information

This role is managed through a partner company, which will review applications and handle the next steps in the hiring process.

The selection process uses AI-assisted matching to evaluate candidates quickly, consistently, and fairly against the core role criteria. A shortlist is then passed to the hiring company, whose internal team manages interviews, assessments, and final decisions.

By applying, candidates agree that the platform may process personal data to assess candidacy and share relevant details with the employer, based on legitimate interest and pre-contractual measures under applicable data protection laws, including GDPR. Applicants may exercise rights such as access, correction, deletion, and objection at any time.

Artificial intelligence tools may also be used to support parts of the recruitment process, such as reviewing applications, analyzing resumes, and checking responses for inconsistencies or verification signals. These tools assist recruiters but do not replace human judgment, and final hiring decisions are made by people.