Additional Skills:<br><br>Deep hands-on expertise with dbt (Cloud or Core), including model development, testing, macros, packages, documentation, scheduling, and performance optimization.<br>Strong command of dbt project structure, materializations (including incremental models and snapshots), and integration with BI-owned metric certification and semantic layers.<br>Ability to evaluate when to leverage community dbt packages versus building custom solutions.<br>Expert-level SQL for complex analytical transformations and performance optimization.<br>Strong data modeling skills across dimensional (Kimball), Data Vault, and domain-oriented patterns, including temporal modeling, SCDs, and surrogate keys.<br>Proven judgment in balancing normalization vs. denormalization for performance, flexibility, and downstream analytics use cases.<br>Experience designing and implementing automated data quality testing and validation frameworks.<br>Familiarity with data quality tooling (e.g., Great Expectations) and core data quality dimensions across analytics workflows.<br>Familiarity with modern analytics stacks and how analytics engineering integrates with cloud data platforms, ingestion tools, dbt, and BI systems.<br>Working knowledge of DataOps practices such as version control, CI/CD, and automated testing.<br>Knowledge of K–12 education data domains and metrics, including enrollment, attendance, assessments, staffing, and multi-state reporting requirements.<br>Familiarity with education data privacy (FERPA), academic calendars, and operational rhythms.<br>Proven ability to lead technical teams, facilitate requirements and design discussions, and manage competing stakeholder priorities.<br>Strong communication and change management skills, translating technical capabilities into clear business value. <br> <br><br>Required experience:<br><br>Bachelor’s degree in Computer Science, Information Systems, Data Science, Statistics, Mathematics, or a related field, or equivalent practical experience.<br>7+ years of experience in analytics engineering, data engineering, data analytics, or closely related technical roles.<br>3+ years of experience in technical leadership or people management, leading analytics, data, or BI teams.<br>Demonstrated hands-on experience with dbt (2+ years) building and maintaining production data models and transformations.<br>Strong data modeling expertise, with a proven track record designing dimensional models, analytics data marts, or business-facing data products.<br>Expert-level SQL skills, including complex analytical queries and performance optimization<br>Experience partnering with non-technical stakeholders to gather requirements and translate them into effective technical solutions.<br> <br>Preferred Education and Experience:<br><br>Master’s degree in Data Science, Statistics, Computer Science, or a related analytical field.<br>dbt Analytics Engineering certification or equivalent demonstrated expertise<br>Hands-on experience with Snowflake or comparable cloud data warehouse platforms.<br>Experience working with K–12 education data, student information systems, or education analytics.<br>Experience building data solutions for multi-state or geographically distributed organizations.<br>Exposure to data governance practices, including business glossaries and data quality frameworks<br>Familiarity with modern data stack tools (e.g., ingestion, orchestration, BI, and data quality platforms).<br>Experience leading analytics teams using Agile or iterative delivery methodologies.