Principal Data Engineer

This is a fully remote position, open to applicants in Maine.

📋 Description

• Take ownership and lead the technical strategy and architecture for the DI&T analytics data platform and its semantic layer.

• Design and create scalable data models and curated datasets.

• Define and oversee the analytics semantic layer, encompassing business logic, metrics, dimensions, relationships, and definitions.

• Lead the development of reliable production data pipelines and transformation processes.

• Integrate data from operational systems, data warehouses, integration hubs, data lakes, and enterprise sources.

• Translate business and analytical needs into scalable, reusable data solutions.

• Address complex cross-system data challenges and devise innovative solutions.

• Establish and enforce data modeling, engineering, and governance standards.

• Implement validation, testing, monitoring, and error handling to guarantee data quality and reliability.

• Provide technical leadership and guidance to analysts, engineers, and technical team members.

• Act as a subject matter expert in data modeling, dbt, Snowflake, SQL, and analytics engineering.

• Monitor pipeline and model performance while implementing sustainable enhancements.

• Collaborate with technology and engineering teams to advance data architecture.

• Identify opportunities to centralize data, automate workflows, enhance integration, and fortify the data foundation.

• Establish technical priorities that align with business goals.

• Articulate technical concepts, risks, trade-offs, and recommendations to both technical and non-technical audiences.

⛳️ Requirements

• Bachelor’s degree in computer science, data engineering, information systems, or a related field; an equivalent combination of education and relevant experience will be considered.

• 7+ years of experience in data engineering, analytics, data architecture, or a similar technical field.

• Proven technical leadership in production data platforms or enterprise-scale analytics environments.

• Extensive experience with dbt or a comparable tool.

• In-depth experience with Snowflake or a similar analytical platform.

• Advanced knowledge of dimensional, wide-table, and hybrid modeling techniques.

• Exceptional SQL skills.

• Experience in production data engineering, including pipelines, orchestration, monitoring, error handling, and operational support.

• Strong proficiency in Git and CI/CD practices.

• Proficiency in Python or another scripting language is preferred.

• Familiarity with AI-assisted development tools is preferred.

• Ability to assess technical trade-offs and make architectural decisions.

• Capability to influence architecture and system design across organizational boundaries.

• Proficient in translating complex technical concepts for both technical and non-technical stakeholders.

• Strong understanding of data governance, data lineage, business definitions, naming conventions, metadata, and context engineering.

• Ability to work autonomously and prioritize tasks with minimal guidance.

• Strong problem-solving abilities for complex, ambiguous, and novel technical challenges.

• Cloud and data engineering certifications are preferred, but not required.

🏝️ Benefits

• Opportunity for an annual cash bonus.

• Health, Dental, and Vision Benefits available from Day One.

• 5% matching 401k.

• Financial support.

• Pet insurance.

• Mental health resources.

• Paid days off for volunteering.

• Employee stock program.

• Matching donations to foundations.

• Competitive compensation and incentives.

• Positive and respectful work culture.

• Opportunities for learning and discovery.