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DPR is looking to solve the technical direction of data engineering and analytics initiatives by hiring an experienced Snowflake Data Engineer

Requirements

• Proven expertise in data analysis, data modeling, and data engineering with a focus on cloud- native data platforms.
• Hands-on experience with secure and scalable enterprise data architectures using Microsoft Azure or AWS.
• Deep knowledge of Snowflake and DBT, with experience building robust data ingestion and ETL/ELT pipelines.
• Experience in designing data structures for data lakes and cloud data warehouses to support analytics and reporting.
• Strong proficiency in SQL, python and git.
• Familiarity with agile methodologies, and experience working closely with cross functional teams to manage technical backlogs.
• Skilled in orchestrating and automating data pipelines within a DevOps framework.

Responsibilities

• Design, build, and own the overall data architecture across the Snowflake data platform —including the data lake, data warehouse, and data consumption layers.
• Develop, optimize, and manage conceptual and logical data architectures and integrations across both internal and external systems.
• Experiment with and prototype solutions using the latest Snowflake features, demonstrating practical use cases and driving early adoption across the business.
• Collaborate closely with engineering, data, and analytics teams to deliver business-critical data solutions.
• Drive high priority data initiatives using Azure/AWS as well as Snowflake & DBT.
• Design scalable, secure, and high-performance data pipelines to support evolving business needs.
• Design, build and own data models, data flows, and integration patterns for the data lake, data warehouse, and consumption data layers

Other

• 5+ years of experience in a senior data engineering role, designing and delivering solutions at scale in cloud environments.
• Strong communicator with the ability to present ideas clearly and influence stakeholders — with a passion for enabling data-driven transformation.
• Ability to work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads.
• Ability to participate in all phases of the project lifecycle and lead data architecture initiatives.
• Ability to partner with strategic customers to understand their vision and ensure future requirements are incorporated into the platform roadmap.