Data Engineer

Role Summary

We are seeking a Data Engineer to design, build, and operate data pipelines and warehouses powering

enterprise analytics and reporting. The role covers ingestion, transformation, modelling, and operationalisation

across cloud and on-prem data sources.

Key Responsibilities

• Design and implement batch + streaming data pipelines (ETL/ELT).
• Build and maintain dimensional/data-warehouse models (Star/Snowflake schema, slowly-changing
  
  
  

dimensions).

• Develop in SQL, Python, and at least one orchestrator (Airflow, Azure Data Factory, AWS Glue).
• Operate data quality checks, lineage, and observability (Great Expectations, Monte Carlo, or similar).
• Optimise warehouse performance (Snowflake, Synapse, BigQuery, Redshift).
• Partner with BI/analytics teams on semantic models and self-service consumption.
• Document pipelines, schemas, and runbooks.
  
  
  

Required Qualifications

• Bachelor's degree in CS, Engineering, Statistics, or equivalent.
• 4+ years building production data pipelines.
• Strong SQL (window functions, CTEs, query tuning) and Python.
• Hands-on with at least one major DW/Lakehouse: Snowflake, BigQuery, Synapse, Redshift, Databricks.
• Experience with at least one orchestrator: Airflow, ADF, Glue, dbt + scheduler.
• Familiarity with cloud object storage (S3, ADLS, GCS) and file formats (Parquet, ORC, Avro).
• Professional English — mandatory.
  
  
  

Preferred / Nice To Have

• Working knowledge of Arabic is a plus.
• Streaming experience: Kafka, Kinesis, Event Hubs, Spark Structured Streaming.
• dbt Analytics Engineer or cloud data engineer certifications.
• Exposure to data governance/cataloguing (Purview, Unity Catalog, Collibra).