Head of Data Engineering Riyadh

**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.