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).