The construction company is looking to streamline operations, enhance decision-making, and drive efficiency by developing robust data solutions that support their business goals. They need a Data Engineer to integrate cutting-edge technologies into the construction process.
Requirements
- Minimum of 1-3 years of experience as a Data Engineer, working with cloud platforms (Azure, AWS).
- Strong hands-on expertise in Azure Data Factory, Azure Data Lake, Python, and SQL
- Familiarity with cloud storage (Azure, AWS S3) and integration techniques (APIs, webhooks, REST).
- Experience with modern data platforms like Snowflake and Microsoft Fabric.
- Solid understanding of Data Modeling, pipeline orchestration and performance optimization
- Strong problem-solving skills and ability to troubleshoot complex data issues.
- Knowledge of Airflow or other orchestration tools.
Responsibilities
- Own data delivery for specific business verticals by translating stakeholder needs into scalable, reliable, and well-documented data solutions.
- Design, develop, and maintain robust data pipelines and ETL processes using tools like Azure Data Factory and Python across internal and external systems.
- Proactively manage data quality, error handling, monitoring, and alerting to ensure timely and trustworthy data delivery.
- Perform debugging, application issue resolution, root cause analysis, and assist in proactive/preventive maintenance.
- Support incident resolution and perform root cause analysis for data-related issues.
- Create and maintain both business requirement and technical requirement documentation
- Collaborate with platform and architecture teams to align with best practices and extend shared data engineering patterns.
Other
- Collaborate with business leaders to understand data needs.
- Work closely with a global engineering team to deliver scalable, timely, and high-quality data solutions.
- Participate in requirements gathering, technical design reviews, and planning discussions with business and technical teams.
- Partner with the extended data team to define, develop, and maintain shared data models and definitions.
- Collaborate with data analysts, business users, and developers to ensure the accuracy and efficiency of data solutions.
