Senior Analytics Engineer
ItsaCheckmate
full-time
Posted on:
Location Type: Remote
Location: India
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Job Level
About the role
- 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
Requirements
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLPythondata modelingA/B testingstatisticshypothesis testingcausal inferencedata transformationELTETL
Soft Skills
systems thinkingmentoringcommunicationcollaborationinfluencinganalytical thinkingproblem-solvingleadershippresentation skillsorganizational skills