At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers. We do this by giving smart, creative, passionate people opportunities to create awesome things.
And that’s where you come in:
We are seeking a dynamic and experienced Manager of Analytics Engineering to lead our team of data analysts and analytics engineers. This individual will play a critical role in shaping the data-driven decision-making process across the organization by building and managing robust analytics infrastructure, ensuring high-quality data, and fostering a collaborative team environment. The ideal candidate is an experienced leader with a strong technical background in analytics engineering and a passion for leveraging data to drive business outcomes.

REQUIRED QUALIFICATIONS:

• Experience:
• Proven experience (5+ years) in data analytics, data engineering, or analytics engineering roles.
• At least 2+ years of leadership or management experience, overseeing teams of analysts and engineers.
• Technical Skills:
• Advanced expertise in dbt, Airflow, and Snowflake.
• Familiarity with relational databases such as PostgreSQL, MySQL, and Redshift is a plus.
• Strong understanding of modern data stack best practices, data modeling, and ETL/ELT workflows.
• Leadership & Communication:
• Excellent leadership and team management skills, with a focus on collaboration and coaching.
• Strong ability to communicate complex technical concepts to non-technical stakeholders.
• Problem-Solving & Strategic Thinking:
• Adept at solving complex data challenges and designing scalable solutions.
• Experience in aligning data strategies with business objectives and KPIs.

PREFERRED QUALIFICATIONS:

• Industry Knowledge:
• Previous experience in the EdTech industry or a strong interest in leveraging data to improve educational outcomes.
• Data-Driven Mindset:
• Proven ability to turn raw data into actionable insights and business value.
• Experience with data visualization tools and advanced analytics techniques is a plus.
  Based on experience
  We’ve always believed in hiring the most awesome people and treating them right. We know that the more diverse we are, the more diverse our ideas will be and when we openly welcome those ideas, our environment is better, and our business is stronger.
  At Instructure we participate in E-Verify and yes, in case you didn’t catch it from the above, we are an Equal Opportunity Employer.
  All Instructure employees are required to successfully pass a background check upon being hired

• Team Leadership & Development:
• Manage and mentor a team of data analysts and analytics engineers, fostering professional growth and skill development.
• Set team goals, define key performance metrics, and ensure timely delivery of projects.
• Promote a culture of collaboration, continuous improvement, and innovation within the team.
• Analytics Infrastructure & Engineering:
• Oversee the design, development, and optimization of data pipelines, data models, and transformation workflows using dbt, Airflow, and Snowflake.
• Collaborate with cross-functional teams to identify and prioritize analytics engineering initiatives aligned with business objectives.
• Implement best practices for data governance, security, and performance to ensure scalable and reliable analytics solutions.
• Data Strategy & Execution:
• Partner with stakeholders to translate business needs into data and analytics solutions.
• Define and execute strategies for integrating, modeling, and transforming data from diverse sources, including PostgreSQL, MySQL, and Redshift.
• Drive insights by enabling advanced analytics and reporting, supporting business teams in making informed decisions.
• Technical Expertise & Hands-On Contribution:
• Provide hands-on expertise in dbt, Airflow, and Snowflake, guiding the team in best practices and troubleshooting complex data challenges.
• Stay current with industry trends and emerging technologies, ensuring the team is leveraging the most effective tools and methodologies.
• EdTech Collaboration (Preferred):
• Leverage prior experience or interest in the EdTech industry to tailor data strategies that align with the unique needs of educational technology products and services.