Data Engineer

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

You will build and look after the pipelines that move data from the client's operational systems into the warehouse, and the data models that everything downstream depends on. Ingestion, processing and modelling, plus the documentation that goes with them. You will also do the analyst work that keeps the numbers honest.

What you will do

• Profile new sources before you build: databases, APIs, files, open data, structured and unstructured.
• Build, schedule and monitor ingestion and processing pipelines in the tools the client already uses, and extend them where it makes sense.
• Design and build the warehouse models (star schemas, conformed dimensions) that dashboards and machine-learning use cases sit on.
• Put data-quality checks and lineage capture into every pipeline, and keep the conceptual, logical and physical model documentation current.
• Work with business owners to reconcile figures and define KPIs, and help write the monthly progress report.

What you need

• Strong Python and SQL, used in production
• Spark (Databricks or Hadoop) and BigQuery, and comfort with both data-lake and warehouse patterns
• Hands-on experience with at least two of Talend, Informatica, NiFi and Denodo
• Extracting and capturing changes from MS SQL Server, Oracle, MySQL and PostgreSQL
• Ingesting from APIs, files (SFTP, Excel, CSV) and open data, in batch and streaming
• Dimensional modelling: star schemas, conformed dimensions, slowly changing dimensions, and the ability to document models at conceptual, logical and physical level
• Orchestration, monitoring, retries, data-quality checks and lineage
• Profiling, reconciliation, defining KPIs with business users

Good to have

• dbt, Airflow, Dataflow, Iceberg
• Google Professional Data Engineer or Databricks certificatio