As Senior Go-to-Market Analytics Engineer at Mews, you'll architect the data infrastructure that powers revenue growth across our expanding hospitality platform. You'll lead the transformation of how we understand customer journeys, optimize sales processes, and scale our business through data-driven insights. Working closely with data teams across Product, Finance, and Operations, you'll build bridges between siloed data sources to create a unified view of our business performance. This role offers the unique opportunity to architect our data ecosystem while navigating the exciting challenges of integrating new business systems and newly acquired companies into our platform.✅ Your mission, should you choose to accept it:Data Architecture
Design and implement scalable go-to-market data models in dbt (our data modeling tool) and Databricks (our data warehouse) that unify customer insights across sales, marketing, and customer success
Lead data governance initiatives that enable secure, efficient data sharing between teams while maintaining data quality standards
Present data insights and architectural recommendations to leadership, translating technical concepts into business impact
M&A Integration & System Consolidation
Orchestrate data integration for newly acquired products and companies, transforming fragmented systems into our unified platform
Design migration strategies that preserve historical data integrity while modernizing legacy architectures
Technical Leadership & Mentorship
Mentor junior analytics engineers through coaching, code reviews, pair programming, and technical documentation
Foster a culture of continuous learning by sharing knowledge across data teams and organizing cross-team technical sessions
Guide the team's adoption of emerging technologies, like AI-driven development and data self-service, while maintaining focus on business value delivery
🤝 You'll be a great fit if you bring a few of the below with youMust-Have Qualifications
5+ years of experience as an Analytics Engineer, Data Engineer, or similar role with demonstrated impact on business outcomes
Expert-level SQL skills with proven ability to optimize complex queries on billion-row datasets
Advanced Python experience in data pipeline automation and advanced analytics
Production experience with dbt, including advanced features like incremental models, macros, and testing frameworks
Hands-on experience with modern cloud data warehouses (e.g., Databricks, Snowflake, BigQuery)
Track record of building collaborative relationships with cross-functional teams and translating business needs into technical solutions
Experience mentoring junior engineers and leading technical initiatives
Strong communication skills with ability to present technical concepts to non-technical stakeholders
Nice-to-Have Qualifications
Experience with Databricks specifically
Background in SaaS companies, particularly those with complex go-to-market motions
M&A data integration experience
Familiarity with Power BI or similar business intelligence tools
Experience with AI-powered development tools (Cursor, Claude Code, GitHub Copilot, or similar)
Knowledge of data governance frameworks and privacy regulations (GDPR, CCPA)
