Analytics Engineer

• Design, build, and maintain scalable data models in Amazon Redshift to support reporting, dashboards, and ad hoc analysis.
• Collaborate with data engineering teams to expand and optimize the analytics warehouse architecture.
• Establish and enforce standards for schema design, naming conventions, and data lineage.
• Develop, maintain, and optimize data pipelines that deliver clean and reliable data to business users.
• Partner with stakeholders to gather requirements and translate business needs into scalable data solutions.
• Create and maintain comprehensive data documentation, including metrics definitions and transformation logic.
• Support BI platforms by ensuring analytics-ready datasets and assisting with dashboard development.
• Monitor data quality and implement testing, alerting, and validation processes to ensure warehouse reliability.
• Identify opportunities to improve data accessibility, consistency, and usability across the organization.
• Promote best practices in analytics engineering, including version control, code reviews, and reproducible workflows.

Analytics Engineer – Digital Media

• Participate in vendor scoping sessions to finalize full table and field requirements before the build phase begins.
• Model a dedicated datamart in the dbt transformations marts layer, sourcing data from core order, line item, and customer tables.
• Translate vendor schema specifications into specific internal field mappings, accurately accounting for DTC-adjusted logic such as ship-to addresses, order dates, and customer grain.
• Configure Snowflake data sharing and connections to facilitate seamless vendor ingestion.
• Write comprehensive dbt tests and documentation for all delivered models to ensure long-term data quality and transparency.
• Manage the full merge request workflow using GitLab, adhering to strict peer review processes before deployment.

Senior Analytics Engineer – ETL/ELT

Senior Analytics Engineer – ETL/ELT Focused

• Implement the curated data model layer in dbt across 18 data domains, working closely with the Onshore Analytics Engineering Lead.
• Design and build dbt models across the full layered architecture: staging, intermediate, and mart layers.
• Implement comprehensive dbt testing strategies, including unique, not_null, accepted_values, relationships, and custom tests to ensure data quality and reliability.
• Develop and optimize incremental models to handle high-volume domains processing billions of events efficiently.
• Generate and maintain thorough project documentation, including column descriptions and lineage graphs, to support transparency and team collaboration.

• Build and Optimize Data Pipelines
• Develop and maintain scalable data pipelines using dbt, Amazon Redshift, and orchestration tools such as MageAI
• Collaborate with cross-functional teams to translate business logic into reliable and efficient data models
• Design and Maintain Data Models
• Support the design and optimization of data models focused on analytics, reporting, and credit-related use cases, ensuring scalability, consistency, and performance
• Ensure Data Quality and Reliability
• Maintain high data integrity through validation processes, monitoring, testing, and regular audits across datasets and pipelines
• Automate and Improve Processes
• Contribute to process automation and infrastructure improvements to increase efficiency and reduce manual work within the data platform
• Generate Insights and Enable Decision-Making
• Collaborate with business and technical stakeholders to deliver analytical datasets and reporting that support strategic decision-making within the Credit team
• Collaborate and Grow Through Best Practices
• Work closely with Analytics Engineers, Data Scientists, and Business stakeholders while continuously improving coding standards, documentation, and data modeling practices

Analytics Engineer – Credit

• Design and implement a multi-tier SaaS reporting infrastructure to support diverse client levels and brand campaign requirements.
• Lead the GA4 and Google Tag Manager strategy, overseeing implementation, QA, and the definition of event tracking standards for QR scans, lead captures, and promo engagement.
• Architect and manage GA4 data exports into BigQuery, building robust models that join event data with account, venue, and subscription datasets.
• Integrate data from diverse sources including Sanity CMS, Mailchimp, SMS platforms, and POS systems to create a unified view of the consumer journey.
• Develop reusable reporting templates and automated dashboards for client recaps, monthly summaries, and real-time campaign performance.
• Evaluate and deploy reporting automation tools such as Looker Studio Pro, AgencyAnalytics, or Whatagraph to enhance scalability.
• Establish data governance and access control protocols to ensure secure, account-specific reporting views.
• Partner with product and engineering teams to ensure tracking requirements are seamlessly integrated into the development lifecycle.
• Translate complex analytics into actionable business insights for internal stakeholders, venues, and brand partners.
• Maintain comprehensive documentation including tracking plans, data dictionaries, and architectural workflows.

Senior Data Analytics Engineer – Hospitality Tech

• Design, develop, and implement end-to-end systems (ETL, APIs, and integrated applications)
• Build scalable ETL pipelines for high-volume batch and real-time data processing
• Develop applications using Java, Python, and Spring-based frameworks
• Design and maintain RESTful APIs and API documentation (Swagger/OpenAPI)
• Integrate messaging and streaming solutions (e.g., ActiveMQ, RabbitMQ)
• Apply object-oriented principles and troubleshoot across application and data layers
• Containerize and deploy solutions using Docker/Kubernetes in cloud environments (AWS/Azure)
• Ensure application security using OWASP standards and best practices
• Collaborate with clients to gather requirements and deliver technical solutions
• Produce technical documentation, system designs, and process flows
• Support testing, deployment, and continuous improvement efforts

Senior Developer, Systems & ETL Engineer

• We are looking for a Lead Analytics Engineer to join our data team.
• Reporting to the Hiring Manager, you will be responsible for applying data engineering best practices to analytics code to transform, test, and document data.
• You will provide clean and organized data sets to end users.
• You will be provide expert code reviews and mentorship to other engineers in the data space
• You will be responsible for building and maintaining composable data models, as well as optimizing SQL query performance for the models you build.
• You will transform raw data into business insights, working closely with stakeholders and developing analyses to answer critical business questions.
• You will create data visualizations and help stakeholders explore and understand the data visualization tools available to them.

Lead Analytics Engineer – Data Team

• Build and maintain the presentation layer to provide aggregated, clean, and trustworthy data to the rest of the company.
• Constantly seeking ways to improve our data infrastructure.
• Provide self-service and training to the rest of the company and bring data accessibility to a new level.

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