About the Role
We’re looking for a Data Engineer who’s passionate about building reliable, scalable, and cost-efficient data systems. You’ll work with a modern stack, Kafka, Google Cloud Platform (GCP), AWS, to design and maintain the pipelines that power analytics, machine learning, and product insights.
Ideal role for someone with solid foundational skills in data engineering who’s ready to deepen their expertise, take ownership of workflows, and collaborate across teams.
If you don’t know every tool in our stack yet, that’s okay. We value curiosity, problem-solving, and a willingness to learn just as much as existing technical skills.
What's On Your Plate?
Design, build, and maintain data pipelines and workflows for batch and streaming use cases.
Work with Kafka to manage real-time data ingestion and event-driven architectures.
Leverage GCP and AWS services for storage, processing, and orchestration (, BigQuery, Dataflow, S3, Lambda).
Orchestrate workflows using tools like Airflow or similar schedulers.
Ensure data quality and reliability through monitoring, alerting, and automated validation.
Collaborate with analysts, data scientists, and product teams to understand requirements and deliver data solutions that drive business impact.
Optimize for cost and performance across cloud environments.
Participate in code reviews, documentation, and knowledge sharing to raise the bar for the team.
Our Tech Stack
Data Ingestion & Streaming: Apache Kafka, Kafka Connect
Cloud Platforms: Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Cloud Storage), AWS (S3, Lambda, Glue)
Workflow Orchestration: Apache Airflow
Programming Languages: Python, SQL, (bonus: Java/Scala)
Infrastructure & DevOps: Terraform, CI/CD pipelines, Docker
Monitoring & Observability: Grafana, Prometheus, Cloud-native tools
Qualifications
What Did We Order?
What We’re Looking For
Experience (1-3 years) in data engineering, software engineering, or a related field.
Proficiency in SQL and at least one programming language (Python preferred).
Understanding of data modeling, ETL/ELT concepts, and cloud-based data warehouses.
Familiarity with streaming platforms (Kafka, Kinesis, or similar).
Comfort working in cloud environments (GCP, AWS, or Azure).
Strong communication skills, able to explain technical concepts to non-technical audiences.
Growth mindset, eager to learn, adapt, and take on new challenges.
Nice-to-Have (But Not Required and willing to learn)
Experience with infrastructure-as-code (Terraform, CloudFormation).
Exposure to containerization (Docker, Kubernetes).
Knowledge of data governance, security, and compliance best practices.
Data Engineer II • Dubai, Dubai, AE
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