Senior Analytics Engineer

Checkmate builds the operating system for digital ordering in restaurants, powering integrations between POS systems, delivery platforms, and restaurant brands. Our products sit at the center of how millions of orders move across systems every day making experimentation, automation, and ML-driven optimization central to our competitive advantage.

We operate at the intersection of product, data, and restaurant operations where analytical rigor directly drives revenue growth, product innovation, and customer experience.

We are seeking a Senior Analytics Engineer who combines strong data engineering fundamentals with advanced analytical thinking and business acumen.

This role is not just about building pipelines it’s about designing the analytical foundation that powers product decisions, experimentation, and machine learning initiatives. You will translate complex restaurant operational and customer behavior data into scalable, reliable, and insight-ready data models that drive measurable business impact.

You will act as a bridge between engineering, analytics, product, and data science ensuring our data platform supports both robust technical systems and high-quality decision-making.

• Translate ambiguous business questions into structured analytical frameworks
• Develop KPI definitions, metric layers, and standardized reporting logic across teams
• Partner with Product and Growth teams to define success metrics and measurement strategies
• Deliver deep-dive analyses on ordering behavior, churn risk, marketplace performance, and operational efficiency
• Present insights and trade-offs clearly to senior stakeholders and leadership

• Own and scale A/B testing infrastructure, including experiment tracking and evaluation pipelines
• Define best practices for hypothesis testing, power analysis, sequential testing, and causal inference
• Build experimentation dashboards and automated reporting systems
• Partner with Data Science to productionize predictive models and design reusable ML-ready datasets
• Support feature engineering and monitoring for production ML systems

• Design and maintain scalable ELT/ETL workflows that power analytics, experimentation, and ML use cases
• Build and optimize dimensional data models (star schemas, data vault, etc.) to enable self-service analytics
• Create trusted, well-documented datasets for product, finance, operations, and growth teams
• Improve data quality, observability, lineage, and governance across the analytics ecosystem
• Optimize performance across warehouse and transformation layers.
• Drive best practices in analytics engineering across the organization

• Influence tooling decisions (Airflow, dbt, Snowflake, Spark, etc.) with scalability and business usability in mind
• Mentor analytics engineers and elevate modeling and measurement standards
• Champion a data-driven culture grounded in experimentation and measurable impact

• 7+ years of experience in analytics engineering, data engineering, or advanced analytics roles
• Deep expertise in SQL and modern data modeling techniques
• Strong proficiency in Python (or similar) for data transformation, statistical analysis, and ML integration
• Experience working with modern data stack tools (e.g., Airflow, dbt, Snowflake, BigQuery, Redshift, Spark)
• Proven experience building scalable data warehouse environments

• Strong understanding of statistics, hypothesis testing, and causal inference
• Experience designing and operating A/B testing frameworks
• Ability to define metrics, KPIs, and experimentation standards across teams
• Experience supporting production ML workflows or predictive modeling initiatives
• Strong systems thinking with the ability to connect technical decisions to business outcomes

• Experience in restaurant technology, POS systems, or digital ordering platforms
• Exposure to customer lifecycle analytics, marketplace analytics, or growth experimentation
• Familiarity with real-time data pipelines (e.g., Kafka or similar)
• Experience mentoring engineers or leading cross-functional initiatives

• You’ll shape the analytical backbone of a fast-scaling product ecosystem
• Your work will directly influence revenue, product strategy, and customer experience
• You’ll operate at the intersection of engineering rigor and business decision-making
• You’ll help build experimentation and ML systems that power millions of restaurant transactions daily