Head of Data Engineering [Riyadh]

Talent Seed
London
3 days ago
Create job alert

**This role requires relocation to Riyadh, KSA**


As the Head of Data, you will play a crucial role in shaping our data strategy and driving data-driven decision-making across the organisation. You will lead our data initiatives, oversee the data lifecycle, and ensure that our data infrastructure supports our rapid growth and innovation in the SaaS industry.


Data Engineering & Infrastructure

  • Architect and scale a robust data platform that supports both internal and product-facing use cases.
  • Build and maintain secure, efficient, and scalable ETL/ELT pipelines to ingest and transform data from various sources.
  • Own the data warehouse and data lake architecture (e.g., Snowflake, BigQuery, Redshift) and ensure data availability, integrity, and performance.
  • Introduce infrastructure-as-code, CI/CD pipelines, and observability best practices into the data platform.
  • Ensure compliance with data security, privacy, and governance standards (e.g., GDPR, SOC 2).


Data Science & Analytics Support

  • Partner with data science and product teams to support the deployment of ML models and statistical analysis.
  • Enable experimentation frameworks and predictive insights for HR-focused product features (e.g., retention prediction, engagement scoring).
  • Collaborate with BI/analytics teams to ensure scalable access to clean, trusted data across the business.
  • Champion self-service analytics by providing tools, documentation, and data literacy support.


Leadership & Strategy

  • Build and lead a high-performing, multidisciplinary data team (data engineers, analytics engineers, data scientists).
  • Define and drive the company’s data strategy in alignment with product and business objectives.
  • Act as a key partner to executive stakeholders, translating data opportunities into business impact.
  • Balance hands-on technical leadership with mentorship and strategic planning.


What We’re Looking For

  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
  • 10+ years of experience in data engineering or platform roles, including at least 3 years in a leadership position.
  • Deep hands-on expertise in modern data architecture, pipelines, and tooling (e.g., Airflow, DBT, Kafka, Spark, Python, SQL).
  • Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and scalable data systems.
  • Familiarity with analytics and ML workflows, including model deployment and monitoring.
  • Experience leading data teams in fast-paced, agile SaaS environments.
  • Bonus: Experience working in HR tech, people analytics, or adjacent HR data domains.
  • Excellent stakeholder communication and the ability to align data initiatives with strategic goals.
  • Proven ability to foster a collaborative and high-performance team culture.


Nice to Have

  • Experience integrating data with customer-facing SaaS products or embedded analytics.
  • Exposure to ML/AI platforms and pipelines (e.g., model serving, feature stores).
  • Familiarity with data visualisation tools (e.g., Looker, Tableau, Metabase).
  • Experience with SaaS business models, metrics, and product data is highly desirable.

Related Jobs

View all jobs

Head of Data Engineering

Head of Data Engineering

Global Head of Data Engineering - £250k tc

Global Head of Data Engineering

Senior Data Solutions Designer

Senior Data Solutions Designer

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write a Winning Cover Letter for Machine Learning Jobs: Proven 4-Paragraph Structure

Learn how to craft the perfect cover letter for machine learning jobs with this proven 4-paragraph structure. Ideal for entry-level candidates, career switchers, and professionals looking to advance in the machine learning sector. When applying for a machine learning job, your cover letter is a vital part of your application. Machine learning is an exciting and rapidly evolving field, and your cover letter offers the chance to demonstrate your technical expertise, passion for AI, and your ability to apply machine learning techniques to solve real-world problems. Writing a cover letter for machine learning roles may feel intimidating, but by following a clear structure, you can showcase your strengths effectively. Whether you're just entering the field, transitioning from another role, or looking to advance your career in machine learning, this article will guide you through a proven four-paragraph structure. We’ll provide practical tips and sample lines to help you create a compelling cover letter that catches the attention of hiring managers in the machine learning job market.

Veterans in Machine Learning: A Military‑to‑Civilian Pathway into AI Careers

Introduction Artificial intelligence is no longer relegated to sci‑fi films—it underpins battlefield decision‑support, fraud detection, and even supermarket logistics. The UK Government’s 2025 AI Sector Deal forecasts an additional £200 billion in GDP by 2030, with machine‑learning (ML) engineers cited as the nation’s second most in‑demand tech role (Tech Nation 2024). The Ministry of Defence’s Defence AI Strategy echoes that urgency, earmarking £1.6 billion for FY 2025–28 to embed ML into planning, logistics, and autonomous systems. If you have ever tuned a radar filter, plotted artillery trajectories, or sifted sensor data for actionable intel, you have already worked with statistical modelling—the backbone of machine learning. This guide shows UK veterans how to reframe military experience for ML roles, leverage MoD transition funding, and land high‑impact positions building the models shaping tomorrow’s defence and commercial landscapes. Quick Win: Bookmark our live board for Machine‑Learning Engineer roles to see who’s hiring today.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.