Data Engineer-Job Description
Department: IT
Division: Application
Title : Data Engineer
Reports To :Application Manager
Location : Riyadh.
Main Duties:
Data Engineer is responsible for designing, developing, and maintaining scalable data pipelines and infrastructure that support data-driven decision-making across the organization. The role focuses on ensuring that data is efficiently collected, stored, integrated, and made accessible for analytical and operational use. Data Engineers collaborate with cross-functional teams to translate data requirements into reliable technical solutions while upholding standards for data quality, performance, and security.
Responsibilities:
- Design and develop data pipelines (ETL/ELT) to efficiently collect, transform, and load data from various sources into data warehouses or data lakes.
- Design, build, and optimize robust data pipelines and ETL/ELT processes using Data Factory, Synapse Data Engineering (Spark), and Notebooks within Microsoft Fabric.
- Build and maintain data infrastructure, including databases, APIs, and cloud-based storage solutions.
- Develop and implement scalable Lakehouse and Warehouse architectures using Fabric's data warehousing capabilities and Delta Lake standards to ensure data integrity and performance.
- Integrate data from multiple systems to create a unified and consistent view of business information.
- Ensure data quality, accuracy, and consistency through validation, cleansing, and governance practices.
- Implement and maintain data security measures, including access controls, encryption, and compliance with security policies.
- Support data governance initiatives by defining data standards, metadata, lineage, and documentation practices.
- Participate in data management activities such as data cataloging, master data management (MDM), and data lifecycle management.
- Develop analytical tools, frameworks, and systems to support business intelligence and data science objectives.
- Collaborate with data analysts and data scientists to optimize data accessibility, workflows, and model deployment.
- Monitor system performance, identify and resolve data pipeline or infrastructure issues, and optimize database queries.
- Automate repetitive and manual data processes to enhance operational efficiency and scalability.
- Document data workflows, architecture, schemas, and design standards for internal use and future reference.
- Stay current with emerging technologies, tools, and best practices in data engineering, data governance, big data, and analytics.
Requirements
- Bachelor's degree (or equivalent) in Computer Science, Information Technology, Engineering, or a related field.
- 24 years of experience in data engineering, data management, or database systems development.
- Proficiency in programming languages such as Python, SQL, or Java.
- Experience working with relational database technologies (e.g., MySQL, PostgreSQL, SQL Server).
- Familiarity with ETL tools, data integration frameworks, and pipeline orchestration platforms (e.g., Airflow, Talend, Apache NiFi).
- Understanding of cloud data platforms (e.g.,MS Fabric, Databricks) and modern data warehousing technologies (e.g.,Databricks, MS Fabri, Redshift, BigQuery, Snowflake).
- Strong knowledge of data modeling, data governance practices, and information security principles.
- Eagerness to learn and willingness to dive deep into data validation
- Possession of DP-600 or DP-70 certification is considered an advantage
Skills:
SQL, Python, R, Spark, ETL/ELT, Data Pipelines, Microsoft Fabric, Data Integration, Data Modeling, Data Warehousing, Data Orchestration, Data Quality, Data Governance, Cloud Platforms, Power BI, Dashboard Development, Data Analysis, Problem Solving, Communication Skills, Critical Thinking
