Senior Analytics Engineer

Recruiting from Scratch is representing a leading EdTech company that is building next-generation curriculum and assessment programs. They are seeking a Senior Analytics Engineer to design, build, and maintain analytical data models to support reporting and business decisions while collaborating with various stakeholders to enhance learning outcomes.

Responsibilities:

• Design, build, and maintain analytical data models, adhering to Kimball principles, to support reporting and business decisions
• Write and optimize complex SQL queries across large datasets, leveraging CTEs, window functions, and multi-table joins for performance and clarity
• Develop well-documented and tested transformation logic within a SQL-first ELT framework, preferably using dbt
• Collaborate with stakeholders across product, curriculum, and go-to-market teams to translate business questions into structured, reusable data models
• Own the BI and reporting layer, ensuring models are optimized for consumption by analysts and dashboard tools
• Establish best practices for data modeling, testing standards, and documentation conventions within the analytics engineering workflow
• Proactively identify gaps in data assets and propose improvements to enhance reliability and reduce time-to-insight

Requirements:

• 5–8 years of experience in analytics engineering, BI engineering, or a closely related data role, with a strong focus on data modeling
• Very strong SQL skills, comfortable with complex queries and optimizing for performance and readability
• Proven experience building analytical data models from scratch, including fact/dimension tables and slowly changing dimensions (SCDs)
• Hands-on experience with dbt, including building models, writing tests, and managing dependencies
• Ability to work directly with business stakeholders to understand their questions and develop structured, reliable data models
• Experience in EdTech, SaaS, or mission-driven organizations where data directly influences product and learning outcomes
• Familiarity with BI tools such as Looker or Tableau and understanding how modeling decisions impact downstream visualizations
• Knowledge of data quality frameworks, including schema tests and anomaly detection