Sr Software Engineer, Data & Analytics

Role Overview

Sr. Software Engineer, Data & Analytics (Analytics Engineer) at McGraw Hill / Sharpen. Own the design, development, and maintenance of analytics data pipelines and modeling layers that power insights, decision-making, and personalized experiences.

What You’ll Do

• Design, build, and maintain scalable data pipelines for analytics, reporting, and product insights.
• Develop and optimize the data modeling layer for high performance, maintainability, and usability with analytics/BI tools.
• Collaborate cross-functionally with product, engineering, data scientists/analysts, and business teams to define data requirements and deliver actionable insights.
• Apply data quality, governance, and security best practices across the data infrastructure.
• Drive self-service analytics adoption via clear, user-friendly data models and documentation.
• Evaluate and integrate new data tools/technologies to continuously improve the data stack.
• Monitor and troubleshoot data pipelines to maintain reliability and uptime.
• Partner on KPIs, dashboards, and reporting frameworks to enable data-driven decisions.

What You Bring

• 5+ years of applicable experience (Bachelor’s degree preferred).
• Strong experience with the modern data stack, including dbt and BigQuery.
• Advanced SQL and experience designing/optimizing/maintaining complex data models.
• Experience with ETL/ELT tools/frameworks such as Airflow or Fivetran.
• Experience with event-based analytics platforms such as Segment.
• Solid understanding of data warehousing principles and architecture.
• BI/visualization experience with Tableau or Power BI.
• Scripting/programming experience with Python or R (or similar) for transformation/analysis.
• Knowledge of data governance, compliance, and security.
• Ability to balance engineering rigor with practical business/analytics needs.
• Strong communication skills with technical and non-technical stakeholders.

Preferred Experience & Skills

• Experience in EdTech, startups, or consumer-facing environments.
• Familiarity with observability/performance monitoring tools (e.g., New Relic, Datadog).
• Knowledge of system performance optimization, caching strategies, and distributed systems.