Senior Analytics Engineer - Data Modeling
Posted date [2026-07-02]
(ID: 47339)
 |
Talabat is the MENA region’s leading on-demand delivery platform, headquartered in Dubai and operating across eight markets. We leverage a tech-driven flywheel model to connect millions of users with food, groceries, and essential services. By bridging the gap between people and local businesses, we continue to scale our ecosystem and simplify everyday life through innovation. |
Job Description and Requirements
Senior Analytics Engineer - Data ModelingJob Snapshot
Role: Senior Analytics Engineer - Data Modeling
Location: Dubai, United Arab Emirates
Industry: Internet
Function: Database Development-Administration
Experience: Strong experience in analytics engineering, data modeling, SQL, Python, dbt, and cloud data platforms
Job Type: Full-time
Position Overview
Senior Analytics Engineer - Data Modeling in Dubai, United Arab Emirates is an Internet hiring opportunity for a technically strong data professional who can transform raw information into reliable, scalable, and business-ready data models for Talabat. This role supports smarter decision-making across product, operations, commercial, finance, and customer experience teams by building clean SQL and dbt models, improving data quality, supporting self-service analytics, and making trusted data easier for analysts, data scientists, and business stakeholders to use.
Job Details
Country: United Arab Emirates
City: Dubai
Industry: Internet
Function: Database Development-Administration
Salary: 25000-42000
Estimated salary range based on similar jobs in the
job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Job Type: Full-time
Role Context
The Senior Analytics Engineer - Data Modeling will help Talabat build a stronger data foundation by converting complex raw datasets into structured, documented, tested, and accessible data assets. The role sits between data engineering, analytics, data science, and business teams, making sure data pipelines, transformation logic, reporting layers, and analytical models are accurate and scalable. By improving data reliability and usability, the position enables faster insights, better business intelligence, stronger product decisions, and more intelligent platform experiences for customers, partners, and riders.
Key Responsibilities
* Design, build, and maintain clean, efficient, and scalable data models using SQL, dbt, and modern analytics engineering practices.
* Transform raw data into structured datasets that support business intelligence, self-service analytics, reporting, and advanced analysis.
* Optimize SQL queries, transformation workflows, and data processing logic to improve speed, cost efficiency, and reliability.
* Work closely with data engineers to define data requirements and strengthen ETL or ELT pipelines across cloud-based data platforms.
* Partner with product analysts, data scientists, business teams, and operational stakeholders to ensure datasets answer real reporting and decision-making needs.
* Develop and maintain data transformation workflows using dbt, SQL, Python, and cloud warehouse environments.
* Implement data quality rules, automated checks, validation routines, and reconciliation processes to improve accuracy and consistency.
* Monitor data integrity and investigate data issues before they affect dashboards, reporting, or business decisions.
* Troubleshoot pipeline failures, model errors, freshness delays, and data discrepancies with a structured and proactive approach.
* Build data models that are easy to understand, reusable, well-documented, and aligned with agreed business definitions.
* Support the development of semantic layers, reporting-ready tables, and standardized metrics for cross-functional analytics.
* Automate data validation, reporting support processes, and recurring data checks where possible.
* Advocate for strong documentation, testing, version control, peer review, and maintainable analytics workflows.
* Use Git and CI-CD practices to support reliable deployment, controlled changes, and collaborative data development.
* Contribute to performance improvement, data governance, and model design standards across analytics engineering workstreams.
* Help teams move from manual reporting and fragmented data use toward trusted, scalable, and reusable data products.
Ideal Profile
* Bachelor’s degree in Engineering, Computer Science, Technology, Data, or a similar field.
* Postgraduate qualification in a relevant field is a plus but not required.
* Strong proficiency in SQL and Python for data transformation, modeling, automation, and analytical workflows.
* Hands-on experience with dbt for data modeling, testing, documentation, and transformation workflow management.
* Experience working with cloud-based data warehouses such as Snowflake, BigQuery, Google Cloud Platform, Redshift, or similar platforms.
* Good understanding of data engineering principles, including ETL, ELT, data pipelines, data lineage, and warehouse design.
* Familiarity with Git, version control, code review, and CI-CD practices for data workflows.
* Strong ability to translate business requirements into reliable data models, reporting tables, and reusable analytical datasets.
* Practical experience improving data quality, query performance, model reliability, and analytics documentation.
* Comfortable working with analysts, data scientists, data engineers, and business stakeholders in a fast-paced technology environment.
* Strong problem-solving skills with the ability to investigate data issues, identify root causes, and implement durable fixes.
* Detail-oriented working style with a clear focus on accuracy, consistency, scalability, and maintainability.
* Able to communicate technical concepts clearly to both technical and non-technical stakeholders.
* Interested in building intelligent data foundations that improve customer, partner, rider, and business decision-making.
Skills Set
* Analytics engineering
* Data modeling
* SQL
* Python
* dbt
* Data transformation
* ETL
* ELT
* Cloud data warehouses
* Snowflake
* BigQuery
* Google Cloud Platform
* Redshift
* Data pipeline support
* Query optimization
* Data quality testing
* Automated validation
* Data integrity monitoring
* Business intelligence support
* Self-service analytics
* Reporting datasets
* Semantic data models
* Data documentation
* Version control
* Git
* CI-CD
* Data troubleshooting
* Data governance support
* Performance optimization
* Stakeholder collaboration
* Product analytics support
* Data science enablement
Why Join Us
This role offers a strong opportunity to work at the center of Talabat’s data and technology growth in Dubai. The Senior Analytics Engineer - Data Modeling will help shape the trusted data layer behind customer insights, product intelligence, operational performance, restaurant partner analytics, rider-related decisions, and business reporting. Talabat offers exposure to large-scale delivery data, modern cloud data platforms, high-impact analytics projects, and a performance-driven culture where strong data foundations directly influence smarter decisions across the region.
About the Company
Talabat is a leading on-demand food delivery and q-commerce platform serving customers, restaurant partners, local shops, and riders across the MENA region. Founded in Kuwait and now part of Delivery Hero Group, Talabat uses technology, data, logistics, and local market knowledge to simplify everyday delivery. In Dubai, the company continues to invest in intelligent platform capabilities, analytics, grocery delivery, restaurant growth, rider operations, and customer-focused digital innovation.
Gender: Any
Candidate Nationality: Any
Job Type: Full-time
Role Context
The Senior Analytics Engineer - Data Modeling will help Talabat build a stronger data foundation by converting complex raw datasets into structured, documented, tested, and accessible data assets. The role sits between data engineering, analytics, data science, and business teams, making sure data pipelines, transformation logic, reporting layers, and analytical models are accurate and scalable. By improving data reliability and usability, the position enables faster insights, better business intelligence, stronger product decisions, and more intelligent platform experiences for customers, partners, and riders.
Key Responsibilities
* Design, build, and maintain clean, efficient, and scalable data models using SQL, dbt, and modern analytics engineering practices.
* Transform raw data into structured datasets that support business intelligence, self-service analytics, reporting, and advanced analysis.
* Optimize SQL queries, transformation workflows, and data processing logic to improve speed, cost efficiency, and reliability.
* Work closely with data engineers to define data requirements and strengthen ETL or ELT pipelines across cloud-based data platforms.
* Partner with product analysts, data scientists, business teams, and operational stakeholders to ensure datasets answer real reporting and decision-making needs.
* Develop and maintain data transformation workflows using dbt, SQL, Python, and cloud warehouse environments.
* Implement data quality rules, automated checks, validation routines, and reconciliation processes to improve accuracy and consistency.
* Monitor data integrity and investigate data issues before they affect dashboards, reporting, or business decisions.
* Troubleshoot pipeline failures, model errors, freshness delays, and data discrepancies with a structured and proactive approach.
* Build data models that are easy to understand, reusable, well-documented, and aligned with agreed business definitions.
* Support the development of semantic layers, reporting-ready tables, and standardized metrics for cross-functional analytics.
* Automate data validation, reporting support processes, and recurring data checks where possible.
* Advocate for strong documentation, testing, version control, peer review, and maintainable analytics workflows.
* Use Git and CI-CD practices to support reliable deployment, controlled changes, and collaborative data development.
* Contribute to performance improvement, data governance, and model design standards across analytics engineering workstreams.
* Help teams move from manual reporting and fragmented data use toward trusted, scalable, and reusable data products.
Ideal Profile
* Bachelor’s degree in Engineering, Computer Science, Technology, Data, or a similar field.
* Postgraduate qualification in a relevant field is a plus but not required.
* Strong proficiency in SQL and Python for data transformation, modeling, automation, and analytical workflows.
* Hands-on experience with dbt for data modeling, testing, documentation, and transformation workflow management.
* Experience working with cloud-based data warehouses such as Snowflake, BigQuery, Google Cloud Platform, Redshift, or similar platforms.
* Good understanding of data engineering principles, including ETL, ELT, data pipelines, data lineage, and warehouse design.
* Familiarity with Git, version control, code review, and CI-CD practices for data workflows.
* Strong ability to translate business requirements into reliable data models, reporting tables, and reusable analytical datasets.
* Practical experience improving data quality, query performance, model reliability, and analytics documentation.
* Comfortable working with analysts, data scientists, data engineers, and business stakeholders in a fast-paced technology environment.
* Strong problem-solving skills with the ability to investigate data issues, identify root causes, and implement durable fixes.
* Detail-oriented working style with a clear focus on accuracy, consistency, scalability, and maintainability.
* Able to communicate technical concepts clearly to both technical and non-technical stakeholders.
* Interested in building intelligent data foundations that improve customer, partner, rider, and business decision-making.
Skills Set
* Analytics engineering
* Data modeling
* SQL
* Python
* dbt
* Data transformation
* ETL
* ELT
* Cloud data warehouses
* Snowflake
* BigQuery
* Google Cloud Platform
* Redshift
* Data pipeline support
* Query optimization
* Data quality testing
* Automated validation
* Data integrity monitoring
* Business intelligence support
* Self-service analytics
* Reporting datasets
* Semantic data models
* Data documentation
* Version control
* Git
* CI-CD
* Data troubleshooting
* Data governance support
* Performance optimization
* Stakeholder collaboration
* Product analytics support
* Data science enablement
Why Join Us
This role offers a strong opportunity to work at the center of Talabat’s data and technology growth in Dubai. The Senior Analytics Engineer - Data Modeling will help shape the trusted data layer behind customer insights, product intelligence, operational performance, restaurant partner analytics, rider-related decisions, and business reporting. Talabat offers exposure to large-scale delivery data, modern cloud data platforms, high-impact analytics projects, and a performance-driven culture where strong data foundations directly influence smarter decisions across the region.
About the Company
Talabat is a leading on-demand food delivery and q-commerce platform serving customers, restaurant partners, local shops, and riders across the MENA region. Founded in Kuwait and now part of Delivery Hero Group, Talabat uses technology, data, logistics, and local market knowledge to simplify everyday delivery. In Dubai, the company continues to invest in intelligent platform capabilities, analytics, grocery delivery, restaurant growth, rider operations, and customer-focused digital innovation.
