Power International Holding
Data Platform Engineer
Company: Power International Holding
Location: Qatar
Job Type: Full-Time
Job Overview
Power International Holding is looking for a skilled Data Platform Engineer to design, build, and manage scalable enterprise data platforms that power business intelligence, advanced analytics, artificial intelligence (AI), reporting, and automation initiatives. The successful candidate will develop secure, high-performance data solutions that support both real-time and batch data processing while ensuring platform reliability, governance, and operational excellence.
This role requires expertise in modern cloud data platforms, data engineering, automation, and DevOps practices to deliver enterprise-grade data services that enable data-driven decision-making across the organization.
Key Responsibilities
Enterprise Data Platform Development
- Design, implement, and maintain enterprise-scale data lakes, lakehouses, and data warehouse solutions.
- Build scalable cloud-based data platforms using technologies such as Databricks, Snowflake, Azure Synapse, Google BigQuery, or equivalent services.
- Ensure platform reliability, scalability, security, and high availability across development, testing, and production environments.
Data Engineering & Integration
- Develop and maintain efficient ETL and ELT pipelines for structured, semi-structured, and unstructured data.
- Build reusable data ingestion frameworks to streamline enterprise data integration.
- Integrate data from ERP systems, CRM applications, APIs, databases, flat files, IoT devices, and streaming data sources.
- Support both real-time and scheduled data processing workloads.
Workflow Automation & DevOps
- Implement and manage workflow orchestration tools such as Apache Airflow, Azure Data Factory (ADF), Dagster, or similar platforms.
- Develop CI/CD pipelines to automate deployment, testing, and release management for data engineering projects.
- Apply Infrastructure as Code (IaC), containerization, and DevOps best practices to improve operational efficiency.
Data Governance & Security
- Implement enterprise data security controls, role-based access, encryption, and compliance standards.
- Enable metadata management, data cataloging, lineage tracking, and governance capabilities.
- Support enterprise data quality initiatives through monitoring, validation, and governance frameworks.
Performance & Platform Optimization
- Monitor platform performance, storage utilization, and resource consumption.
- Optimize SQL queries, Spark workloads, compute resources, and data pipelines for maximum efficiency.
- Troubleshoot production issues and implement proactive measures to ensure platform stability and minimal downtime.
Backup & Disaster Recovery
- Manage development, testing, staging, and production environments following controlled release processes.
- Implement backup, recovery, disaster recovery, and business continuity strategies for critical enterprise data assets.
- Ensure platform resilience and operational readiness.
Analytics & AI Enablement
- Deliver optimized datasets and data models that support business intelligence dashboards, analytics, AI, and machine learning initiatives.
- Prepare feature-ready datasets for predictive analytics and AI applications.
- Enable secure and reliable data access for reporting, automation, and enterprise decision-making.
Collaboration & Continuous Improvement
- Collaborate with data architects, software engineers, AI teams, analysts, and business stakeholders to enhance enterprise data capabilities.
- Recommend modern technologies, tools, and engineering practices that improve platform scalability, reliability, and cost efficiency.
- Contribute to enterprise data platform standards, governance policies, and modernization initiatives.
Required Skills & Qualifications
- Strong understanding of modern data architectures, including Data Lakes, Lakehouses, Data Warehouses, and Medallion Architecture.
- Extensive experience with cloud data platforms such as Databricks, Snowflake, Azure Synapse Analytics, Google BigQuery, or similar technologies.
- Advanced knowledge of SQL, Python, Apache Spark, and distributed data processing frameworks.
- Experience developing ETL/ELT pipelines and enterprise data integration solutions.
- Hands-on experience with workflow orchestration platforms such as Apache Airflow, Azure Data Factory (ADF), Dagster, or equivalent.
- Familiarity with DevOps practices, CI/CD pipelines, Infrastructure as Code (Terraform, ARM, or similar), and container technologies.
- Strong understanding of data governance, metadata management, lineage, data cataloging, and security best practices.
- Excellent analytical, troubleshooting, and performance optimization skills.
- Strong communication and stakeholder collaboration abilities.
Experience Requirements
- Minimum 5–10 years of experience in Data Engineering, Data Platform Engineering, Big Data, or Data Warehousing.
- Proven experience designing and supporting enterprise cloud data platforms and large-scale data ecosystems.
- Experience delivering data solutions for analytics, artificial intelligence (AI), business intelligence, automation, and enterprise reporting.
- Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related discipline is preferred.
Why Join Power International Holding?
Become part of a forward-thinking technology team driving enterprise data transformation across the organization. You’ll work with modern cloud technologies, advanced analytics platforms, AI initiatives, and scalable data architectures while contributing to innovative digital solutions that create measurable business value.
To apply for this job please visit careers.powerholding-intl.com.