Data Engineer
Riyadh, Riyadh Province, Saudi Arabia · Full Time
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- Experience
- 5+ yrs
- Salary
- —
- Openings
- 1
- Posted
- 14 hours ago
- Work mode
- In office
- Resume
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Job description
About Acuative
Acuative is a global provider of technology services specializing in advanced networking, IT solutions, and digital transformation for enterprise, service provider, and public sector clients. Operating with a strong presence regionally, the company has a proven record in handling large, mission-critical projects. Acuative emphasizes deep technical knowledge combined with a customer-focused service culture and is currently growing its data and analytics division.
Role Summary
The Data Engineer will be instrumental in constructing and maintaining the data pipelines that power an enterprise Lakehouse and business intelligence initiative. This role involves designing automated data ingestion flows, building efficient ETL/ELT systems, enhancing data transformations for optimized performance and cost, and ensuring data quality and reliability throughout the platform.
Key Responsibilities
- Create and sustain automated pipelines for ingesting data from diverse source systems.
- Design and expand reusable ETL/ELT frameworks in line with platform architecture principles.
- Develop and refine data transformation scripts and jobs focusing on boosting performance and reducing costs.
- Apply data quality controls, validation procedures, and monitoring mechanisms to all pipelines.
- Manage pipeline orchestration and scheduling using technologies such as Azure Data Factory or Apache Airflow.
- Work collaboratively with architecture and business intelligence teams to produce well-prepared analytics datasets.
- Maintain thorough documentation of pipelines, frameworks, and operational processes.
Required Qualifications
- Minimum of five years’ experience in data engineering roles.
- Strong skills in Python, SQL, and Apache Spark.
- Hands-on experience with cloud-based data tools and current data platform technologies.
- Familiarity with pipeline orchestration platforms like Azure Data Factory and Apache Airflow.
- Comprehensive knowledge of data quality management along with ETL and ELT best practices.
Preferred Qualifications
- Hands-on experience with Lakehouse technologies such as Databricks, Synapse, or Snowflake.
- Understanding of continuous integration and DevOps methodologies applied to data pipeline development.
- Relevant certifications in cloud computing or data engineering domains are advantageous.