DPR Construction is looking to develop robust data solutions to support business goals and enhance operational efficiency by integrating cutting-edge technologies into the construction process.
Requirements
- 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
- Knowledge of Airflow or other orchestration tools.
- Experience working with Git-based workflows and CI/CD pipelines
- Familiarity with tools like Power BI for data visualization
Responsibilities
- Design, develop, and maintain robust data pipelines and ETL processes using tools like Azure Data Factory and Python across internal and external systems.
- Translate business requirements into technical requirements
- Create and maintain technical documentation related to data architecture, integration flows, and processes.
- Monitor and troubleshoot pipeline performance and reliability with minimal oversight
- Collaborate with other engineers, delivery leads and platform teams to ensure data solutions meet business needs while following best practices
- 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.
Other
- Minimum of 1-3 years of experience as a Data Engineer, working with cloud platforms (Azure, AWS).
- Excellent communication skills, with the ability to work collaboratively in a team environment and support business stakeholders
- Experience working with or coordinating with overseas teams is a strong plus
- DMV Applicants: In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required.
- Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance.
