It’s Plein Air Agency is a leading marketing consultancy focusing on the restaurant and hospitality industry providing solutions from Creative, Production, Media Strategy & Buying, Digital Content to Website and Mobile App development. We are a fully remote agency and are looking for remote talent to join our team!

The Analytics Engineer is responsible for designing, building, and maintaining the data pipelines, models, and infrastructure that power analytics, reporting, and client insights in a fast-paced agency environment. This role sits at the intersection of data engineering and analytics, owning the transformation of raw data into trusted, analytics-ready datasets that support client deliverables and internal decision-making.

This is a hands-on, individual contributor role that partners closely with analytics, guest engagement, media, and technology teams to ensure data is reliable, well-modeled, and delivered on timelines that reflect agency and client needs.

Key Responsibilities

Data Architecture & Modeling

• Design and maintain scalable, analytics-friendly data models that support reporting, dashboards, and client-facing insights
• Establish and evolve modeling standards to ensure consistency, performance, and usability across datasets
• Translate ambiguous business and client requirements into clear, durable data structures

ETL / ELT Pipeline Ownership

• Own the development and maintenance of cloud-based ETL/ELT pipelines from source systems to the data warehouse
• Build and maintain transformations using SQL- and Python-based workflows
• Monitor pipeline health, data freshness, and quality; quickly diagnose and resolve issues that impact analytics or client reporting

Analytics Enablement (Agency-Focused)

• Partner closely with analytics and account teams to ensure datasets are accurate, intuitive, and ready for colleague use
• Support BI tools and semantic layers by delivering trusted source tables and standardized metrics
• Balance speed and rigor, enabling rapid insights while maintaining data integrity

Data Quality, Governance & Documentation

• Implement data quality checks, testing, and validation processes to ensure repeatable results and confidence in client-facing data
• Maintain clear, accessible documentation of sources, transformations, definitions, and assumptions
• Apply version control and deployment best practices to minimize risk in a multi-client environment

Cross-Functional & Client Support

• Collaborate with analytics, engagement, media, and technical teams to understand evolving data needs
• Clearly communicate data limitations, trade-offs, and implications to non-technical stakeholders
• Support client-facing teams by ensuring confidence in data accuracy, methodology, and reporting outputs

Why This Role Is Different

• High-impact, hands-on ownership without people management
• Direct influence on analytics quality and client trust
• Agency pace with modern data tooling and real-world business problems

Professional Development & Growth

• Own and evolve the analytics data foundation supporting high-visibility client work
• Influence data standards, tooling decisions, and best practices across the organization
• Gain exposure to diverse datasets including media, loyalty, POS, and digital engagement

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field — or equivalent practical experience
• 5+ years of experience in data engineering or analytics engineering roles within a cloud environment
• Advanced SQL skills, including complex transformations, performance tuning, and analytical modeling
• Strong Python experience for data transformation, automation, and pipeline support
• Experience working in modern cloud data warehouses (e.g., BigQuery, Snowflake, Redshift)
• Hands-on experience with transformation frameworks such as dbt or similar tools
• Familiarity with orchestration, monitoring, and version control tools (e.g., Airflow, Git)

Preferred / Nice-to-Have Experience

• Experience working in an agency or consulting environment with multiple clients and shifting priorities
• Exposure to restaurant, retail, or multi-location consumer brands
• Experience integrating data from POS systems, loyalty platforms, CRM tools, media platforms, or digital analytics sources
• Experience supporting BI platforms such as Looker, Tableau, or Power BI