Datamatics Technologies
Website:
datamaticstechnologies.com
Company:
https://www.linkedin.com/company/datamatics-technologies
Industries: Wireless Services, Telecommunications, and Communications Equipment Manufacturing
Job details:
Job Description: Data Engineering & Warehousing Engineer
Job Title: Data Engineering & Warehousing Engineer
Experience: 3–11 Years
Location: Riyadh - Onsite
Employment Type: Full-Time
Job Overview
We are seeking a highly skilled Data Engineering & Warehousing Engineer with 3–11 years of experience to design, develop, and maintain scalable data platforms and enterprise data warehouse solutions. The ideal candidate will have hands-on expertise in building ETL/ELT pipelines, data integration, cloud-based data platforms, and big data processing technologies. You will play a key role in enabling reliable, high-performance analytics and business intelligence solutions.
Key Responsibilities
- Design, develop, and optimize scalable ETL/ELT pipelines for structured and unstructured data
- Build and maintain enterprise data warehouses, data lakes, and modern data platforms
- Develop real-time and batch data processing solutions
- Integrate data from multiple internal and external sources while ensuring data quality and governance
- Collaborate with Data Scientists, BI Developers, and business stakeholders to support analytical requirements
- Optimize data storage, query performance, and pipeline reliability
- Implement data security, monitoring, and governance best practices
- Troubleshoot and resolve data pipeline and platform issues
- Participate in architecture discussions and contribute to data platform modernization initiatives
Required Technical SkillsCloud Data Platforms
- Hands-on experience with Google BigQuery and Dataflow and Dataproc and Pub/Sub
- Experience with Azure Synapse and Azure Data Factory
- Experience with Amazon Redshift and AWS Glue
Data Processing & Streaming
- Strong experience with Apache Spark and Apache Kafka
- Experience building batch and real-time data processing pipelines
Data Transformation
- Hands-on experience with dbt or Oracle Data Integrator (ODI) for data transformation and orchestration
- Experience implementing ETL/ELT best practices and reusable data models
Databases & Data Warehousing
- Strong experience with Oracle or PostgreSQL
- Expertise in SQL, relational database design, performance tuning, and query optimization
Data Engineering
- Experience with data modeling, data governance, metadata management, and data quality frameworks
- Knowledge of dimensional modeling and modern data warehouse architectures
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or a related field
- 3–11 years of professional experience in Data Engineering, Data Warehousing, or Big Data technologies
- Strong programming and scripting skills using SQL, Python, or similar languages
- Excellent analytical and problem-solving abilities
- Experience working in Agile/Scrum development environments
Preferred Skills
- Experience with cloud-native data lake and lakehouse architectures
- Knowledge of CI/CD pipelines and Infrastructure as Code (IaC)
- Familiarity with containerization technologies such as Docker and Kubernetes
- Experience supporting machine learning and analytics workloads
- Cloud certifications on AWS, Microsoft Azure, or Google Cloud Platform are a plus
Key Technology Stack
- Google Cloud Data Services: BigQuery and Dataflow and Dataproc and Pub/Sub
- Azure Data Services: Azure Synapse and Azure Data Factory
- AWS Data Services: Amazon Redshift and AWS Glue
- Data Processing: Apache Spark and Apache Kafka
- Data Transformation: dbt or Oracle Data Integrator (ODI)
- Databases: Oracle or PostgreSQL
- Programming: SQL and Python
- Cloud Platforms: Google Cloud Platform or Microsoft Azure or Amazon Web Services (Preferred)
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