Analytics Engineer - Data Modeling and Analytics

Talabat Holding; Dubai; Presencial; AED 180 000 - 260 000; Tempo integral

Resumo da oferta

talabat is seeking an Analytics Engineer to build a reliable, scalable data foundation for analytics and BI. You will transform raw data into well-structured analytical models using SQL and dbt, enabling product analysts and data scientists to make informed decisions.

You will work closely with Data Engineering and Analytics teams to optimize queries and ensure data quality for business insights. This on-site role in Dubai requires collaboration across stakeholders to support self-service

Qualificações

• Minimum 3 years hands-on data modeling using dbt.
• Strong SQL and Python skills for analytics and data transformation.
• Experience with cloud-based data warehouses (Snowflake, BigQuery, Redshift).
• Hands-on dbt experience for data modeling and transformation.
• Familiarity with Git for version control and CI/CD practices.
• Understanding of data modeling to support BI and analytics.

Responsabilidades

• Design, develop and maintain scalable analytical data models using SQL and dbt.
• Transform raw data into structured datasets supporting analytics and BI.
• Develop reusable data models to improve consistency and accessibility.
• Optimize SQL queries and data transformation processes for performance.
• Maintain data models as business needs evolve and ensure reliability.
• Collaborate with Data Engineers to align models with data structures.
• Support self-service analytics and reports for stakeholders.

Conhecimentos

SQL

dbt

Python

Cloud data warehouses

Git

CI/CD

Data modeling

ETL/ELT

Formação académica

Bachelor's degree in Engineering/CS

Postgraduate degree advantageous

Ferramentas

Snowflake

BigQuery

Redshift

GCP

Git

Descrição da oferta de emprego

Analytics Engineer - Data Modeling and Analytics Job Snapshot - Role: Analytics Engineer - Location: Dubai, United Arab Emirates - Industry: Internet - Function: Database Development-Administration - Experience: 3 years of hands‑on data modeling experience using dbt - Job Type: Full Time - Work Arrangement: On-site

talabat is looking for an Analytics Engineer to help build a reliable, scalable and accessible data foundation for its analytics and business intelligence needs. In this role, you will transform raw data into well-structured analytical models that enable product analysts, data scientists and business stakeholders to make informed decisions. You will work extensively with SQL, dbt and cloud-based data warehouses to develop efficient data transformation workflows, improve query performance and maintain high data quality standards. Working closely with Data Engineering and Analytics teams, you will help make data easier to discover, understand and use across talabat 's business.

Job Details

Country: United Arab Emirates

City: Dubai

Industry: Internet

Function: Database Development-Administration

Salary: Not disclosed

Gender: No Preference

Candidate Nationality: Not specified

Job Type: Full Time

Work Arrangement: On-site

Data Modeling and Transformation

• Design, develop and maintain clean, efficient and scalable analytical data models using SQL and dbt.
• Transform raw data into structured datasets that support analytics, reporting and business intelligence.
• Develop reusable data models that improve consistency and accessibility across analytical workflows.
• Optimize SQL queries and data transformation processes to improve performance and processing efficiency.
• Maintain data models as analytical requirements and business needs evolve.
• Ensure data structures are suitable for reliable downstream analysis.

Self-Service Analytics and Business Intelligence

• Structure data to support self-service analytics and business intelligence applications.
• Make analytical datasets accessible and understandable for relevant business and technical stakeholders.
• Work with analysts to ensure transformed data supports meaningful insights and reporting.
• Improve the consistency and usability of data available for analytical purposes.
• Help teams work with reliable information when evaluating product and business performance.

Data Engineering Collaboration

• Partner with Data Engineers to define data requirements and improve data processing workflows.
• Contribute to the enhancement of Extract, Transform and Load (ETL) pipelines.
• Apply an understanding of ETL and Extract, Load and Transform (ELT) principles to analytical data preparation.
• Coordinate with engineering teams to ensure data models align with underlying data structures.
• Support scalable and maintainable data transformation practices.

Cross-Functional Analytics Support

• Collaborate with Product Analysts, Data Scientists and business teams to understand their analytical requirements.
• Translate reporting and analysis needs into appropriate data models.
• Ensure analytical datasets provide the information required for business decision-making.
• Work with stakeholders to identify data usability challenges and opportunities for improvement.
• Support alignment between data engineering capabilities and business analytics requirements.

Data Quality and Reliability

• Implement and maintain data quality practices that improve accuracy and consistency.
• Develop automated data validation processes to identify data issues.
• Monitor data integrity and investigate inconsistencies proactively.
• Troubleshoot problems affecting data models and analytical outputs.
• Work with relevant teams to resolve data quality issues and improve reliability.
• Promote consistent testing and validation practices across data transformation workflows.

Workflow Automation and Engineering Standards

• Build and maintain data transformation workflows using dbt, SQL and cloud-based data platforms.
• Automate appropriate data validation and reporting activities.
• Apply documentation standards that make data models easier to understand and maintain.
• Advocate for effective testing and version control practices.
• Use Git and relevant CI/CD practices to support reliable changes to data workflows.
• Contribute to continuous improvements in data modeling efficiency, maintainability and engineering quality.

What Did We Order

Education

• Bachelor 's degree in Engineering, Computer Science, Technology or a similar field.
• A postgraduate degree is an advantage but is not required.

Professional Experience

• Minimum 3 years of hands‑on experience in data modeling using dbt.
• Practical experience developing and maintaining analytical data models.
• Experience working with data transformation workflows and analytical data environments.

Technical Skills

• Strong proficiency in SQL and Python.
• Hands‑on experience using dbt for data modeling and transformation.
• Ability to write efficient SQL queries and optimize analytical data processing.
• Experience working with cloud-based data warehouses or data platforms such as Snowflake, BigQuery, Google Cloud Platform (GCP) or Amazon Redshift.
• Familiarity with Git for version control.
• Understanding of Continuous Integration and Continuous Delivery (CI/CD) practices for data workflows.
• Knowledge of data engineering principles, including ETL and ELT processes.

Data Quality and Analytics Understanding

• Ability to develop structured, reliable datasets for analytical use.
• Understanding of data validation, consistency and integrity.
• Familiarity with testing and documentation practices for analytical data models.
• Ability to identify and troubleshoot issues affecting data accuracy.
• Understanding of how data models support business intelligence, product analytics and data science.

Collaboration and Problem-Solving

• Ability to work effectively with Data Engineers, Analysts, Data Scientists and business stakeholders.
• Strong analytical thinking and technical problem-solving capabilities.
• Attention to detail when developing, testing and maintaining data models.
• Ability to understand analytical requirements and translate them into practical data solutions.
• Commitment to producing reliable, maintainable and accessible analytical data.

About talabat

Founded in Kuwait in 2004, talabat is an on-demand food delivery and quick-commerce platform serving customers across eight countries in the region. The company uses technology and local market knowledge to simplify everyday deliveries, support restaurants and local shops, and provide earning opportunities for riders. With more than 6,000 employees, talabat is focused on building a high-performance culture through employee engagement, talent development and innovation. The company has received multiple Great Place to Work awards. As talabat continues developing its digital platform, reliable analytics and well-structured data play an important role in understanding customers, improving operations and supporting informed business decisions.