Analytics Engineer

About Us: The Center for Education Market Dynamics (CEMD) is on a mission to improve academic outcomes for underserved students by expanding access to high-quality curriculum and instruction. As a leading nonprofit in K–12 market intelligence, we believe that better data leads to better decisions, and ultimately, better opportunities for students. At CEMD, we work to equip education leaders with the insights they need to make informed, strategic choices about curriculum and instructional materials. We serve as a trusted hub for K–12 education data, making complex information accessible, actionable, and impactful. We do this by: Developing a comprehensive K–12 dataset to track curriculum selection trends across districts. Sharing insights for the public good to inform strategy, policy, and decision-making. Providing tools and services that help districts and education leaders take strategic, data-driven actions on behalf of students. We are a passionate and collaborative team that values curiosity, action, and impact. If you're excited about using the power of data to shape the future of education, we'd love to have you join us! CEMD is a fiscally sponsored project of Cambiar Education. About the Role The Analytics Engineer brings technical expertise and creative problem-solving to expand and refine how we collect, structure, and analyze data at scale. This role emphasizes building automated, reliable data collection systems and transforming raw information into well-modeled, analysis-ready datasets that power internal tools and partner insights. You will own key parts of the data lifecycle, from ingestion and transformation through modeling and quality assurance, ensuring our data is structured, trustworthy, and scalable. What you’ll do: Build scalable, automated data collection systems Design, implement, and continuously improve automated data collection workflows and operational methodologies. Develop systematic approaches to gather curriculum adoption information from diverse sources. Build and maintain automations using APIs, web scraping, scheduled jobs, and document parsing to reduce manual effort and increase coverage. Improve pipeline reliability through logging, monitoring and error handling processes. Design and maintain robust data models Transform raw inputs into clean, structured, analysis-ready datasets using reproducible transformation workflows. Create and maintain clear documentation for data structures, transformation logic, and operational workflows. Ensure data reliability and quality Establish quality control processes including validation rules, deduplication logic, completeness checks, and audit trails. Partner with stakeholders to define and track key metrics such as coverage, freshness, confidence, and data completeness. Troubleshoot and improve data collection operations to maintain continuous, reliable data flow. Support analytics and product development Collaborate to translate modeled data into meaningful insights for partners and clients. Contribute technical expertise to internal and external facing tools by improving underlying schemas and dataset performance. This role is for you if: A systems thinker who can design clean, scalable data models from messy, real-world inputs. A builder who enjoys automating workflows and improving operational efficiency. A quality-focused analyst who prioritizes data integrity and consistency. A proactive self-starter who can navigate ambiguity and drive projects forward. A strong communicator who can clearly document schemas, definitions, and technical decisions. A collaborative partner comfortable working cross-functionally with analysts, researchers, product, and leadership. Preferred Experience: Experience working in the K–12 education ecosystem (districts, state agencies, or organizations serving the K–12 market). 3+ years of experience in data engineering, analytics engineering, data operations, or market research systems. Strong proficiency in SQL, including complex joins, aggregations, window functions, and performance tuning. Proficiency in Python, R, or similar for automation and data transformation. Experience designing and maintaining relational data models and analysis-ready tables. Experience with automated data collection methods (APIs, scraping, scheduled pipelines). Experience with workflow orchestration tools (Airflow, n8n, Make). Familiarity with version control (Git/GitHub) and documentation best practices. Bachelor’s degree or equivalent practical experience.

About Us: The Center for Education Market Dynamics (CEMD) is on a mission to improve academic outcomes for underserved students by expanding access to high-quality curriculum and instruction. As a leading nonprofit in K–12 market intelligence, we believe that better data leads to better decisions, and ultimately, better opportunities for students. At CEMD, we work to equip education leaders with the insights they need to make informed, strategic choices about curriculum and instructional materials. We serve as a trusted hub for K–12 education data, making complex information accessible, actionable, and impactful. We do this by: Developing a comprehensive K–12 dataset to track curriculum selection trends across districts. Sharing insights for the public good to inform strategy, policy, and decision-making. Providing tools and services that help districts and education leaders take strategic, data-driven actions on behalf of students. We are a passionate and collaborative team that values curiosity, action, and impact. If you're excited about using the power of data to shape the future of education, we'd love to have you join us! CEMD is a fiscally sponsored project of Cambiar Education. About the Role The Analytics Engineer brings technical expertise and creative problem-solving to expand and refine how we collect, structure, and analyze data at scale. This role emphasizes building automated, reliable data collection systems and transforming raw information into well-modeled, analysis-ready datasets that power internal tools and partner insights. You will own key parts of the data lifecycle, from ingestion and transformation through modeling and quality assurance, ensuring our data is structured, trustworthy, and scalable. What you’ll do: Build scalable, automated data collection systems Design, implement, and continuously improve automated data collection workflows and operational methodologies. Develop systematic approaches to gather curriculum adoption information from diverse sources. Build and maintain automations using APIs, web scraping, scheduled jobs, and document parsing to reduce manual effort and increase coverage. Improve pipeline reliability through logging, monitoring and error handling processes. Design and maintain robust data models Transform raw inputs into clean, structured, analysis-ready datasets using reproducible transformation workflows. Create and maintain clear documentation for data structures, transformation logic, and operational workflows. Ensure data reliability and quality Establish quality control processes including validation rules, deduplication logic, completeness checks, and audit trails. Partner with stakeholders to define and track key metrics such as coverage, freshness, confidence, and data completeness. Troubleshoot and improve data collection operations to maintain continuous, reliable data flow. Support analytics and product development Collaborate to translate modeled data into meaningful insights for partners and clients. Contribute technical expertise to internal and external facing tools by improving underlying schemas and dataset performance. This role is for you if: A systems thinker who can design clean, scalable data models from messy, real-world inputs. A builder who enjoys automating workflows and improving operational efficiency. A quality-focused analyst who prioritizes data integrity and consistency. A proactive self-starter who can navigate ambiguity and drive projects forward. A strong communicator who can clearly document schemas, definitions, and technical decisions. A collaborative partner comfortable working cross-functionally with analysts, researchers, product, and leadership. Preferred Experience: Experience working in the K–12 education ecosystem (districts, state agencies, or organizations serving the K–12 market). 3+ years of experience in data engineering, analytics engineering, data operations, or market research systems. Strong proficiency in SQL, including complex joins, aggregations, window functions, and performance tuning. Proficiency in Python, R, or similar for automation and data transformation. Experience designing and maintaining relational data models and analysis-ready tables. Experience with automated data collection methods (APIs, scraping, scheduled pipelines). Experience with workflow orchestration tools (Airflow, n8n, Make). Familiarity with version control (Git/GitHub) and documentation best practices. Bachelor’s degree or equivalent practical experience.