Senior Analytics Engineer

Recruiting From Scratch•Los Angeles, NY

7d•$137,000 - $157,000•Remote

About The Position

We’re representing a leading edtech company building next-generation curriculum, assessment, and learning tools used by millions of students across the United States. Their platform empowers educators and administrators with data-driven insights to improve student outcomes, optimize teaching strategies, and better understand learning progress. With a strong national footprint and mission-driven culture, the company is focused on leveraging data to drive meaningful impact in education at scale. As a Senior Analytics Engineer , you will help design and scale the data systems that power analytics, reporting, and product insights across the organization. You will:

Requirements

5+ years of experience in analytics engineering, data engineering, or software development .
Strong expertise in SQL and analytical data modeling .
Experience with dbt and code-based ETL/ELT frameworks .
Experience building and maintaining data pipelines and warehouse architectures .
Strong understanding of Kimball data modeling principles .
Experience working cross-functionally with data and product teams.
Proficiency with Git and modern development workflows .
Strong written and verbal communication skills.
Bachelor’s degree in Computer Science, Data Science, or equivalent experience.

Nice To Haves

Proficiency in Python or another programming language.
Experience with Snowflake, AWS (S3, RDS, etc.), and Postgres .
Experience with orchestration tools like Airflow .
Familiarity with BI tools such as Looker or Tableau .
Experience with semantic layers like Cube.dev .
Familiarity with metadata tools (e.g., Atlan).
Experience in education or edtech .
Passion for mentorship, teaching, and improving engineering standards.
Interest in building scalable, high-quality data platforms.

Responsibilities

Build and maintain scalable ELT pipelines using dbt and modern data tooling.
Design and optimize data warehouse schemas and SQL transformations.
Develop high-quality analytical data models and metrics for business and product use cases.
Partner with data scientists, analysts, and engineers to ensure reliable and consistent datasets.
Implement best practices around data governance, privacy, and security .
Improve pipeline reliability, testing, and deployment processes.
Contribute to CI/CD workflows, code reviews, and team standards .
Mentor team members and participate in knowledge-sharing initiatives.
Building datasets that track student progress and performance over time .
Designing slowly changing dimension models for complex education systems.
Improving data pipeline efficiency and reliability.