38 Data Engineer jobs in Oman available for remote work from home. Apply for positions such as Data Engineer, Data Engineer , Senior Data Engineer (Data Unification) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design, develop, and maintain scalable data pipelines to integrate data from various source systems like ERP and MES. Collaborate with architects and scientists to transform raw data into high-quality data products for business decision-making.
You will own high-trust data pipelines and analytics models while managing tools like Segment and Mixpanel. You will partner with cross-functional teams to build reliable integrations and maintain scalable data infrastructure.
Design and develop high-volume batch and streaming data ingestion pipelines across AWS and GCP platforms. Lead and mentor junior engineers while collaborating with cross-functional teams to build new product features.
The Lead Data Engineer will design, develop, and maintain robust Spark applications while enforcing coding standards and best practices across the project. They will also collaborate with cross-functional teams to optimize performance and ensure the reliability of enterprise-level data solutions.
The Data Engineer will design, develop, and optimize scalable ETL/ELT processes and data solutions within Google BigQuery. They are responsible for ensuring data consistency, reliability, and auditability across financial and operational reporting domains.
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Design and develop scalable data solutions and Lakehouse architectures using Microsoft Fabric. Build and maintain data pipelines while ensuring data quality and performance optimization for analytics and AI use cases.
Design, build, and optimize cloud-native data pipelines and data warehouses using the Snowflake AI Data Cloud ecosystem. Collaborate with data scientists and analysts to translate business needs into robust technical data models.
You will design, develop, and maintain scalable batch and real-time data pipelines using Python, SQL, and dbt. Additionally, you will manage cloud-based data infrastructure on AWS and collaborate with cross-functional teams to deliver robust data solutions.
You will design, build, and maintain scalable data pipelines while supporting migrations to BigQuery. Additionally, you will orchestrate and optimize data processing workloads to deliver production-grade data products for analytics and business intelligence.
The role involves managing data collection and ingestion pipelines to support AI model training operations. You will collaborate with scientists to optimize data quality and infrastructure costs while shaping the AI team's dataset roadmap.
The role involves managing data collection and ingestion pipelines to support AI model training operations. You will collaborate with scientists to optimize infrastructure for high-quality, large-scale dataset acquisition.
Own and deliver the year-end financial audit data workstream, including transactional data ingestion and reconciliation. Collaborate with accounting stakeholders to resolve data discrepancies and build robust reporting pipelines in Snowflake and Looker.
You will design and build consumable data assets on an AWS data platform while collaborating with product engineering teams to define data ownership and contracts. Additionally, you will onboard data from legacy warehouses and develop tooling to accelerate platform adoption.
You will provide hands-on support for Apache Airflow configuration, DAG development, and troubleshooting while advising customer teams on best practices. Additionally, you will collaborate with internal stakeholders to deliver technical guidance and ensure successful platform adoption and production onboarding.
The role involves managing data collection and ingestion pipelines to support AI model training operations. You will collaborate with scientists to optimize data infrastructure for cost, throughput, and quality.
You will maintain high-volume ingestion pipelines and develop tools and frameworks for the data platform. Additionally, you will support data scientists with production workloads and contribute to ML-platform and streaming initiatives.
The Data Engineer will own and deliver data engineering tasks, integrations, and marketing systems while troubleshooting pipeline and data quality issues. They will collaborate cross-functionally to transform data across various platforms and support payment orchestration flows.
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You will design, build, and maintain scalable data pipelines and infrastructure to ensure high-quality data availability for analytics and data science. Additionally, you will implement MLOps automation and optimize data workflows for performance, cost, and reliability.
Design, develop, and maintain robust Spark applications while enforcing coding standards and best practices across the project. Collaborate with cross-functional teams to deliver scalable software solutions and provide clear communication to stakeholders.
You will design and implement scalable, high-performance reporting solutions and data modeling strategies for large-scale analytical workloads. Additionally, you will provide architectural guidance, mentor engineering team members, and drive best practices in data quality and performance optimization.
Lead the design and orchestration of data engineering solutions and pipelines to disrupt industries and redefine client landscapes. Focus on rendering visualizations for clinical stakeholders and optimizing data lake solutions.
Design, develop, and maintain scalable Spark applications while enforcing coding standards and best practices. Collaborate with cross-functional teams to optimize data handling and ensure the reliability of AI-driven tools.
The Lead Data Engineer will assess data sources, quality, and integration requirements to validate the technical feasibility of AI and reporting use cases. They will provide platform recommendations, identify implementation risks, and support technical documentation for final recommendations.
The Lead Data Engineer will assess data sources and availability to identify ingestion and integration requirements for AI and reporting use cases. They will validate technical feasibility, identify implementation risks, and provide technical documentation and sizing for build activities.
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The Lead Data Engineer will assess data sources and availability to identify ingestion and integration requirements for AI and reporting use cases. They will validate technical feasibility, identify implementation risks, and provide technical documentation and sizing for build activities.
Build and optimize data pipelines using Python, Databricks, and PySpark for batch and real-time processing. Collaborate with stakeholders to deliver end-to-end data products and maintain the analytical database ecosystem.
Lead the design, development, and maintenance of scalable Spark applications while enforcing coding standards and best practices. Provide technical leadership through mentoring, code reviews, and regular communication with the client.
Lead the design, development, and maintenance of scalable Spark applications while enforcing coding standards and best practices. Provide technical leadership through mentoring, code reviews, and regular communication with the client.
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