Data Engineer: Pipelines, Warehousing & Data Quality

Arabic.AI; Riyadh; On-site; SAR 180,000 - 240,000; Full time

Job summary

Arabic.AI is hiring a data engineer to build and maintain pipelines moving data from client systems into a centralized warehouse. You’ll design star schemas and conformed dimensions powering dashboards and ML use cases, while ensuring data quality and lineage across all stages.

You’ll profile sources, implement batch and streaming ingestion, and document models at conceptual, logical and physical levels, working with business users to define KPIs and monthly progress updates.

Qualifications

• Strong Python and SQL, used in production.
• href?
• Spark (Databricks or Hadoop) experience with BigQuery.
• Comfort with data-lake and warehouse patterns.
• Hands-on with at least two of Talend, Informatica, NiFi and Denodo.
• Experience extracting changes from major RDBMS.
• Ingesting from APIs and files in batch and streaming.
• Dimensional modelling and documentation of models.

Responsibilities

• Profile new data sources before building pipelines (databases, APIs, files, open data).
• Build, schedule and monitor ingestion and processing pipelines in client environments.
• Design and implement warehouse models (star schemas, conformed dims) for dashboards and ML use cases.
• Embed data quality checks and lineage in pipelines; maintain documentation.
• Collaborate with business owners to reconcile figures and define KPIs.

Skills

Python

SQL

Spark

BigQuery

APIs

Batch processing

Streaming data

Dimensional modelling

Data quality

KPIs definition

Tools

Talend

Informatica

NiFi

Denodo

dbt

Airflow

Dataflow

Iceberg

Job description

Arabic.AI is hiring a data engineer to build and maintain pipelines moving data from client systems into a centralized warehouse. You’ll design star schemas and conformed dimensions powering dashboards and ML use cases, while ensuring data quality and lineage across all stages.

You’ll profile sources, implement batch and streaming ingestion, and document models at conceptual, logical and physical levels, working with business users to define KPIs and monthly progress updates.