Role Summary
About the job Data Engineer
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
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Design and implement batch + streaming data pipelines (ETL/ELT).
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Build and maintain dimensional/data-warehouse models (Star/Snowflake schema, slowly-changing
dimensions).
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Develop in SQL, Python, and at least one orchestrator (Airflow, Azure Data Factory, AWS Glue).
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Operate data quality checks, lineage, and observability (Great Expectations, Monte Carlo, or similar).
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Optimise warehouse performance (Snowflake, Synapse, BigQuery, Redshift).
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Partner with BI/analytics teams on semantic models and self-service consumption.
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Document pipelines, schemas, and runbooks.
Required Qualifications
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Bachelor's degree in CS, Engineering, Statistics, or equivalent.
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4+ years building production data pipelines.
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Strong SQL (window functions, CTEs, query tuning) and Python.
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Hands-on with at least one major DW/Lakehouse: Snowflake, BigQuery, Synapse, Redshift, Databricks.
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Experience with at least one orchestrator: Airflow, ADF, Glue, dbt + scheduler.
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Familiarity with cloud object storage (S3, ADLS, GCS) and file formats (Parquet, ORC, Avro).
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Professional English — mandatory.
Preferred / Nice To Have
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Working knowledge of Arabic is a plus.
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Streaming experience: Kafka, Kinesis, Event Hubs, Spark Structured Streaming.
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dbt Analytics Engineer or cloud data engineer certifications.
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Exposure to data governance/cataloguing (Purview, Unity Catalog, Collibra).