Tillster

Data Analyst

• Own end-to-end delivery of complex analytical initiatives from business-question framing through execution, presentation, and stakeholder follow-through
• Proactively surface KPI trends, anomalies, opportunities, and risks
• Support ad-hoc analysis for customers, executives, and internal stakeholders with actionable recommendations
• Advise Marketing, Product, Finance, Engineering, Account Management, and Support/Operations
• Design and support statistically valid A/B test experiments
• Serve as the primary Google Analytics subject matter expert for GA4 reporting, custom dimensions and metrics, tracking validation, and warehouse integration
• Design, build, and maintain Looker Explores and dashboards
• Develop, document, and test LookML for owned domains
• Ensure canonical and consistent metric definitions across the semantic layer
• Expand self-service analytics capabilities across business units
• Maintain production Explore and dashboard accuracy as warehouse structures change
• Investigate data-quality issues and partner with Analytics Engineers and Data Engineers on upstream resolution
• Write performant SQL and collaborate on query optimization, compute-cost efficiency, and derived-table design
• Collaborate on LookML architecture and semantic-layer design
• Partner on customer analytics definitions for segmentation, LTV, and churn; accurately surface ML model outputs
• Diagnose data freshness and quality issues in dashboard pipelines
• Own team coding standards, analytical best practices, documentation, and PR review processes
• Mentor Junior Data Analysts and escalate development needs to the Manager
• Build reusable SQL, LookML, analysis, and documentation assets
• Contribute to standards, governance, and best-practice updates
• Apply LLM and AI tools to accelerate analytics workflows
• Design and build self-service analytics agents for natural-language data queries
• Configure Cortex Analyst or equivalent AI-assisted BI platforms
• Define quality standards for AI-generated analytical outputs
• Prototype AI tooling and present build-vs-buy recommendations to the Manager

Senior Data Analyst

• Own end-to-end delivery of complex analytical initiatives from business-question framing through execution, presentation, and stakeholder follow-through
• Proactively identify KPI trends, anomalies, opportunities, and risks
• Support ad-hoc analysis for customers, executives, and internal stakeholders with actionable recommendations
• Advise Marketing, Product, Finance, Engineering, Account Management, and Support/Operations on analytics
• Design and support statistically valid A/B tests, including hypotheses, sample sizing, success metrics, guardrails, and results analysis
• Serve as the primary Google Analytics subject matter expert for GA4 reporting, custom dimensions and metrics, tracking validation, and warehouse integration
• Design, build, and maintain Looker Explores and dashboards
• Develop, document, and test LookML, including dimensions, measures, derived tables, and Explore configurations
• Maintain canonical metric definitions and resolve semantic-layer discrepancies
• Expand self-service analytics for non-technical users across multiple business units
• Monitor data-product accuracy and freshness and resolve upstream data-quality issues with Analytics and Data Engineers
• Write performant SQL and collaborate on query optimization, compute-cost efficiency, and derived-table design
• Partner on semantic-layer architecture and customer analytics for segmentation, LTV, and churn
• Consume Data Science ML outputs and accurately surface them in dashboards and narratives
• Own SQL, LookML, documentation, and code-review standards
• Mentor Junior Data Analysts and contribute reusable analytical assets and best-practice guides
• Apply LLM and AI tools to accelerate analytics workflows
• Design and build natural-language self-service analytics agents
• Configure Cortex Analyst or equivalent AI-assisted BI platforms
• Define validation standards for AI-generated analytical outputs
• Prototype AI tooling and present build-versus-buy recommendations to the Manager

Data Engineer

• Own and maintain data warehouse infrastructure across Redshift, BigQuery, and Snowflake
• Build and maintain real-time, batch, and streaming data pipelines
• Enable data-driven decisions across marketing, product, engineering, sales/account management, finance, and operations
• Design data structures for real-time and near-real-time decision-making
• Support the MarTech stack, including Braze, Acoustic, MoEngage, and Segment
• Modify and maintain SQL and Python ELT processes loading data into Redshift and other warehouses
• Troubleshoot and maintain Airflow/Jenkins orchestration jobs
• Collaborate with DevOps and cloud management on underlying infrastructure
• Fulfill ad-hoc data extract requests
• Provide ad-hoc SQL and analysis support to business stakeholders
• Maintain and update Looker Explores and dashboards
• Partner with Data Analysts on reporting requirements and efficient pipelines and derived tables
• Develop, test, and maintain dbt models
• Unify GA4, CRM, and other data sources into a consolidated warehouse structure
• Build reusable data models for marketing funnels, segmentation, and campaign analytics
• Implement automated data quality checks and validation rules
• Document data models and business logic

Senior Data Analyst

Senior Data Analyst

Senior Data Engineer