Senior Analytics Engineer

A pioneer in K–12 education since 2000, Amplify is leading the way in next-generation curriculum and assessment. Our core and supplemental programs in ELA, math, and science engage all students in rigorous learning and inspire them to think deeply, creatively, and for themselves. Our formative assessment products help teachers identify the targeted instruction students need to build a strong foundation in early reading and math. All of our programs provide educators with powerful tools that help them understand and respond to the needs of every student. Today, Amplify serves more than 15 million students in all 50 states. For more information, visit amplify.com.

Our data analytics teams transform, model, and aggregate the data that empowers our customers to make sense of and tell stories with their data.  You’ll be working with data scientists, data analysts, data engineers, and software engineers to provide clean, accurate, reliable models and metrics for our products.

• Help school administrators build great schools by:

  • Respecting privacy and ensuring security while offering valuable insights 

  • Making inquisitive choices in tech stack, database design, masking policies, and encryption

  • Building analytical models to fuel reporting we offer to administrators

• Helping school principals understand how teachers are teaching and how students are learning by 

  • Architecting data warehouse schemas and SQL transforms with just the right CTEs, window functions, and pivots

  • Creating data solutions using tools like Snowflake, Airflow, DBT, SQL, Python, Cube.dev.

• Learn every day by:

  • Immersing yourself in agile rituals and leveraging our infrastructure

  • Leading collaboration, pull request-ing, CI/CD processes, and mentoring on a cross-functional  team

  • participating in cross-team share-outs, brownbags, and workshop series

  • Becoming an expert in the data models and standards within Amplify to deliver quality and consistent solutions

Example Projects You Might Work On

• Build well-tested and documented ELT data pipelines for full and incremental DBT models to funnel into Cube Semantic Layer models.

• Engineer novel datasets that express a student's progress and performance through an adaptive learning experience that allows for flexible comparison across students and deep analysis of individual students.

• Craft slowly changing dimensional models that take into account the nuances of K-12 education such as School Year changes and students moving schools or classes.

• Improving our pipeline deployments and tests

Required Qualifications:

• BS in Computer Science, Data Science, or equivalent experience.

• 5+ years of professional software development or analytic engineering experience

• Expertise in computer, data, and analytics engineering.

• Expertise in SQL and its use in code-based ETL frameworks, preferably dbt, focusing on reuse and efficiency.

• Expertise in ETL/ELT pipelines, analytical data modeling, aggregations, and metrics

• Expertise in Git and DBT, preferably with automation skills

• Expertise in analytical modeling architectures, including the Kimball design

• Strong communication skills in writing and conversation, including writing engineering training documentation.

Preferred Qualifications: 

• Fluency in a development language such as Python

• Familiarity with metadata management tools such as Atlan

• Experience building dashboards, reports, and models in business intelligence tools such as Tableau or Looker

• Expertise with tools we use every day:

• Storage: Snowflake, AWS Storage Services (S3, RDS, Glacier, DynamoDB) and Postgres

• ETL/ELT: Airflow, dbt, Matillion, Fivetran 

• BI: Cube.dev Looker, Tableau

• Experience with tools we don’t use, but should

• Proven passion and talent for teaching fellow engineers and non-engineers

• Proven passion for building and learning: open source contribu