Data Engineer - Cloud Pipelines

Summary

Build and maintain cloud-based data pipelines for batch and streaming analytics, using Python, SQL, Kafka, Airflow, and GCP/AWS services to power business insights and ML at a fast-growing Q-commerce platform.

Overview

Data Engineer - Cloud Pipelines in Dubai, United Arab Emirates is an Internet industry role focused on building reliable, scalable, and cost-efficient data systems that support analytics, machine learning, product insights, and business decision-making. This opportunity is suited to a growing data engineering professional with strong SQL, Python, cloud platform knowledge, and interest in batch processing, streaming data, workflow orchestration, and modern data infrastructure. The role supports talabat's data ecosystem by designing and maintaining pipelines that move, process, validate, and optimize data across cloud environments. The selected candidate will work with engineers, analysts, data scientists, and product teams to build data workflows that are reliable, well‑monitored, and useful for business teams across a fast‑moving delivery and Q‑commerce platform.

Key Responsibilities

Design, build, and maintain data pipelines for batch processing, streaming use cases, and business analytics.
Work with Apache Kafka and Kafka Connect to support real‑time data ingestion and event‑driven data flows.
Use Google Cloud Platform and AWS services for storage, processing, orchestration, and data movement.
Support cloud‑based data workflows using tools such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, S3, Lambda, and Glue.
Build and maintain workflow orchestration using Apache Airflow or similar scheduling tools.
Write clean and reliable SQL and Python code for data transformation, validation, and pipeline automation.
Improve data quality through monitoring, alerting, automated checks, and validation routines.
Collaborate with analysts, data scientists, product managers, and engineering teams to understand requirements and deliver practical data solutions.
Optimize data systems for performance, scalability, reliability, and cloud cost efficiency.
Participate in code reviews, documentation, and knowledge‑sharing activities to improve engineering standards.
Support troubleshooting of pipeline failures, data delays, quality issues, and performance bottlenecks.
Help maintain clear documentation for pipelines, datasets, workflows, and operational processes.
Contribute to continuous improvement of data engineering practices, tools, and team workflows.

Ideal Profile

1–3 years of experience in data engineering, software engineering, analytics engineering, or a related technical role.
Strong SQL skills with the ability to query, transform, validate, and model data.
Proficiency in at least one programming language, with Python preferred.
Understanding of data modeling, ETL, ELT, cloud data warehouses, and pipeline design concepts.
Familiarity with streaming platforms such as Kafka, Kinesis, or similar technologies.
Comfortable working in cloud environments such as Google Cloud Platform, AWS, or Azure.
Exposure to BigQuery, Dataflow, Pub/Sub, Cloud Storage, S3, Lambda, Glue, or similar cloud services is useful.
Familiarity with Apache Airflow or other workflow orchestration tools is an advantage.
Able to explain technical concepts clearly to non‑technical stakeholders.
Curious, adaptable, and willing to learn new systems, tools, and engineering practices.
Experience with Terraform, CloudFormation, Docker, Kubernetes, data governance, security, or compliance practices is an advantage.

Skills Set

Data engineering
SQL
Python
Apache Kafka
Kafka Connect
Batch data pipelines
Streaming data pipelines
ETL and ELT
Data modeling
Google Cloud Platform
BigQuery
Dataflow
Pub/Sub
Cloud Storage
AWS
S3
Lambda
Glue
Apache Airflow
Terraform
CI/CD pipelines
Docker
Grafana
Prometheus
Data quality monitoring
Cloud cost optimization
Pipeline documentation

Why Join Us

This role offers the chance to work with modern data engineering tools while contributing to systems that influence decisions across a major delivery and Q‑commerce platform. It is a strong opportunity for an early‑career data engineer who wants to grow through hands‑on ownership, mentorship, technical collaboration, and exposure to cloud‑native data architecture. Dubai, United Arab Emirates continues to grow as a regional hub for Internet industry technology, digital commerce, cloud engineering, and data‑driven product development. This position gives the selected candidate the opportunity to build practical data systems, support analytics and machine learning use cases, and develop deeper expertise in scalable data platforms.

About the Company

talabat is a leading on‑demand food and Q‑commerce platform with deep regional roots and operations across multiple MiddleEast markets. Through technology, logistics expertise, and strong local market knowledge, talabat helps customers access everyday deliveries while supporting restaurants, shops, riders, and communities through reliable digital services.

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