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Data Engineer

Acuative Middle East · Riyadh, Saudi Arabia

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About Acuative:Acuative is a global technology services provider delivering advanced network, IT, and digital transformation solutions to enterprise, service provider, and public-sector clients. With a strong regional presence and a track record of delivering large-scale, mission-critical engagements, Acuative combines deep technical expertise with a service-first culture. We are expanding our data and analytics practice and are looking for talented professionals to join a strategic data platform and business intelligence engagement.Role Summary:Acuative is seeking a skilled Data Engineer to build and operate the data pipelines at the heart of an enterprise Lakehouse and business intelligence engagement. You will develop automated ingestion pipelines and ETL/ELT frameworks, optimize data transformations, and ensure that high-quality, reliable data flows through every layer of the platform.Key Responsibilities:Develop and maintain automated data ingestion pipelines from a variety of source systems.Build and extend reusable ETL/ELT frameworks aligned with the platform architecture.Develop and optimize data transformation scripts and jobs for performance and cost efficiency.Implement data quality checks, validation rules, and monitoring across pipelines.Orchestrate and schedule pipelines using tools such as Azure Data Factory or Apache Airflow.Collaborate with the architecture and BI teams to deliver curated, analytics-ready datasets.Document pipelines, frameworks, and operational procedures.Required Qualifications:5+ years of hands-on experience in data engineering.Proficiency in Python, SQL, and Apache Spark.Experience with cloud data tools and modern data platform ecosystems.Practical experience with pipeline orchestration tools (e.g., Azure Data Factory, Apache Airflow).Solid understanding of data quality management and ETL/ELT best practices.Nice to Have:Experience with Lakehouse platforms such as Databricks, Synapse, or Snowflake.Familiarity with CI/CD and DevOps practices for data pipelines.Relevant cloud or data engineering certifications.