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Data Engineer – ETL & Streaming
Data Engineer – ETL & Streaming (Kafka, Airflow, Spark)
Location: UAE
Experience: 4–7 years
Department: Data Engineering
About the Role
We are looking for a Data Engineer to develop robust and scalable data pipelines for both batch and real-time processing using Apache Kafka, Airflow, and Spark. This role focuses on implementing business logic, transformations, and data delivery into data lakes and warehouses.
Key Responsibilities
- Build ETL and ELT pipelines integrating multiple source systems (RDBMS, APIs, events).
- Develop data ingestion and transformation jobs in Spark (PySpark or Scala).
- Design and deploy Airflow DAGs to orchestrate end-to-end data workflows.
- Implement real-time data ingestion and processing using Kafka (streams, connectors, topics).
- Ensure data quality, consistency, and lineage across datasets.
- Collaborate with data modelers and BI teams to deliver curated datasets.
- Troubleshoot pipeline failures, optimize jobs for performance and cost efficiency.
- Work closely with the platform team to integrate pipelines into the enterprise data platform.
- Follow DevOps and CI/CD best practices for deployment and monitoring.
Skills & Qualifications
- Strong programming skills in Python (preferred) or Scala/Java.
- Hands-on experience in Kafka (producers, consumers, stream processing, schema management).
- Proficient in Airflow DAG development, scheduling, and task dependency handling.
- Solid experience with Spark (batch, streaming, dataframes, and optimization).
- Working knowledge of SQL and experience with data modeling (Star/Snowflake).
- Experience with data lake and warehouse environments (Azure Synapse, Databricks, Snowflake, Redshift, etc.).
- Understanding of data versioning, partitioning, and incremental load strategies.
- Familiar with Git-based development, CI/CD, and observability practices.
Job Type: Contract
Contract length: 12 months
Pay: AED15,000.00 - AED30,000.00 per month