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Senior Analytics Engineer

Unlock employer Dubai, United Arab Emirates Posted: 22 Feb 2026

Financial

  • Estimate: $80k - $120k*
  • Zero income tax location

Accessibility

  • Apply from abroad
  • Visa Provided

Requirements

  • Experience: Senior
  • English: Professional

Position

As the leading delivery company in the region, we have a responsibility and opportunity to impact the lives of millions of customers, restaurant partners, and riders. To realize our potential, we need to advance our platform to become much more intelligent in serving our users.

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As a Senior Analytics Engineer, you will be responsible for transforming raw data into well-structured, reliable, and accessible data models that enable analysts, data scientists, and business stakeholders to make informed decisions. Your role will involve:

  • Designing, building, and maintaining clean, efficient, and scalable data models in SQL and dbt while optimizing query performance and data processing efficiency.
  • Ensuring data is structured to support self-service analytics and business intelligence.
  • Collaborating closely with data engineers to define data requirements and enhance ETL pipelines.
  • Partnering with product analysts, data scientists, and business teams to meet analytical and reporting needs.
  • Implementing and enforcing data quality best practices to ensure accuracy and consistency.
  • Developing and maintaining data transformation workflows using dbt, SQL, and cloud-based data platforms, while automating data validation and reporting processes.
  • Monitoring data integrity and proactively troubleshooting data issues, advocating for best practices in documentation, testing, and version control.

Qualifications

  • Bachelor's degree in engineering, computer science, technology, or similar fields; a postgraduate degree is a plus but not required.
  • Strong proficiency in Python, SQL, and experience with dbt for data modeling.
  • Experience with cloud-based data warehouses (e.g., Snowflake, BigQuery, GCP, Redshift).
  • Familiarity with version control (Git) and CI/CD practices for data workflows.
  • Understanding of data engineering principles, including ETL/ELT processes.
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