Data Analyst (Contractor)

Amplify

About The Position

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. As a Data Analyst at Amplify, you will support the Sales team with uncovering insights that shape sales strategy and budget management. Your work will help drive decisions that directly impact the lives of millions of students worldwide. The Sales Finance Operations team provides the financial framework for the Sales leaders to achieve sales targets, including managing commissions, budgets, resource management, and forecasting. The Data Analyst will collect, analyze, and model sales and financial data to identify trends, improve forecasting accuracy, and enhance reporting that drives strategic decision-making. The analyst will work cross-functionally with our centralized Data team to ensure adherence to shared data definitions, share best practices, and communicate insights. This is a contract role.

Requirements

Bachelor’s Degree in Computer Science, Data Science, Statistics, or related field.
2+ years of experience in a data analyst or related role.
2+ years of experience developing dbt data models (designing transformations, writing modular SQL, documenting lineage).
Advanced experience of Excel and Google Sheets with advanced functions and formula creation.
Intermediate to advanced experience with Looker and Snowflake.
2+ years of experience using Python for data analysis (pandas, NumPy).
2+ years of experience using Git and GitHub for version control.
Hands-on experience with cloud-based analytics stacks (e.g., Snowflake, Fivetran).

Nice To Haves

Background in education, edtech, or related field
Experience working with large-scale datasets, statistical analysis, or A/B testing.
Familiarity with additional data visualization tools or advanced BI practices.

Responsibilities

Data Query & Modeling Write advanced SQL queries (complex joins, subqueries, window functions) to extract and validate data.
Develop, maintain, and enhance data models (including DBT models) to support reporting and analytics needs.
Works with ETL/ELT pipelines and relational/dimensional data models to ensure data accuracy and consistency.
Partner with engineers and data scientists to ensure data integrity and alignment across systems.
Analysis & Visualization Gather sales data from various channels to analyze performance, trends and patterns of product penetration, demographics, resource management, and sales trends.
Assist with the calculation of sales commissions.
Provide analytical support required for the development and tracking of sales programs, plans and objectives; attend and participate in sales strategy meetings.
Work closely with sales partners to provide data-driven insights to support sales strategies.
Collect and analyze data to evaluate performance to monthly and annual sales goals, quotas, and forecast; provide explanations for variances and changes to forecasts.
Support process improvement initiatives by developing actionable reports and dashboards for leadership.
Provide ad hoc and customized reporting and recommendations in support of ongoing strategic initiatives.
Build and maintain dashboards and BI reports (e.g., Tableau, Looker) that tell compelling stories with data.
Conduct data profiling and summarization in Python (pandas, NumPy) to uncover trends, anomalies, and distributions.
Apply data visualization best practices to make insights clear and actionable.
Collaboration & Communication Communicate complex findings clearly to non-technical partners through writing, presentations, and conversations.
Contribute to a data-driven culture by helping colleagues understand and leverage key performance metrics.