McGraw Hill is seeking a Sr. Software Engineer - Analytics to build a best-in-class data ecosystem that powers insights, decision-making, and personalized user experiences for their digital learning products.
Requirements
- Strong experience with modern data stack tools (e.g., dbt, BigQuery).
- Strong proficiency in SQL and experience designing, optimizing, and maintaining complex data models.
- Experience with ETL/ELT tools and frameworks (e.g., Airflow, Fivetran, or similar).
- Experience with event-based analytics platforms (e.g., Segment).
- Solid understanding of data warehousing principles and architecture.
- Expertise with business intelligence and visualization tools such Tableau or Power BI.
- Experience with Python, R, or other scripting languages for data transformation and analysis.
Responsibilities
- Design, build, and maintain scalable data pipelines that support analytics, reporting, and product insights.
- Develop and optimize the data modeling layer to ensure high performance, maintainability, and usability for analytics and BI tools.
- Implement best practices for data quality, governance, and security across the data infrastructure.
- Drive adoption of self-service analytics by building clear, user-friendly data models and documentation.
- Evaluate and integrate new data tools and technologies to continuously improve Sharpen’s data stack.
- Monitor and troubleshoot data pipelines, ensuring timely resolution of issues to maintain reliability and uptime.
- Partner with stakeholders to develop KPIs, dashboards, and reporting frameworks that drive data-driven decision-making
Other
- Bachelor's degree in related field or equivalent experience preferred.
- Minimum of 5+ years of applicable experience.
- Knowledge of data governance, compliance, and security best practices.
- Ability to balance engineering rigor with a practical understanding of business and analytics needs.
- Strong communication and collaboration skills to work with technical and non-technical stakeholders.
- Experience in an EdTech, startup, or consumer-facing environment.
- Experience with observability tools like New Relic, Datadog, or equivalent for performance monitoring.
- Strong knowledge of system performance optimization, caching strategies, and distributed systems.
