Position Summary

DPR is seeking an experienced Data Engineer to join our Data Engineering team. This role is part of the Data Engineering and AI team and will ensure DPR is moving towards data-driven decisions based on modern data engineering techniques, applications, and AI. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives. Having experience working with Supply Chain, Procurement, Commercial Construction, Manufacturing, and Prefabrication will be a huge plus.

Responsibilities

Strategic Partnership / Roadmap / Execution / Delivery

• Participate in and collaborate with cross-functional Workgroups and functional teams to align Data Engineering efforts and resources with business goals and objectives.
• Drive strategic conversations with stakeholders to fully understand and document pain points and business requirements, define the key deliverables required to improve business processes, and develop required integrations and apply other data engineering approaches.
• Develop and maintain relationships with business stakeholders and a deep understanding of their processes, tools, and goals.

Data Engineering / Technology / Data Integrations

• Design, build, and maintain robust data pipelines and architectures, ensuring high availability and reliability.
• Develop complex data models and algorithms to extract insights from large Supply Chain, Procurement, and Construction datasets.
• Utilize Snowflake for efficient data storage, data warehousing, and Azure Data Factory for orchestrating and automating data workflows.
• Script and program in Python and use DBT for transformation tasks to optimize data processes.
• Responsibilities include solutions implementation from cloud-first thinking using Agile, Scrum, and Data Ops.
• Assemble data sets that meet functional / non-functional business requirements.
• Design and implement process improvements like automating manual processes, optimizing data pipeline from source to consumption, scaling the data infrastructure, etc.
• Collaborate closely with stakeholders to understand data requirements and translate these into technical solutions.
• Maintain data integrity and compliance, adhering to industry standards and best practices.
• Stay on top of emerging trends and technologies in data engineering and construction tech.