Sr Data Engineer

Overview

At McGraw Hill, we are dedicated to delivering digital learning experiences that transform education for learners and educators. Our focus is on creating seamless, impactful products that truly benefit our users while supporting growth and collaboration across teams. We foster a culture that values innovation, teamwork, and a balance between career growth and personal well-being.

Build the Future

The Senior Data Engineer in Data and Analytics is responsible for advancing McGraw-Hill Education's (MHE) business intelligence and data platform capabilities, delivering scalable, reliable, and actionable insights across financial, product, customer, user, and third-party data domains. This role is deeply hands‑on â designing, building, and optimizing end‑to‑end data pipelines and architectures on AWS (including services such as S3, Glue, Redshift, Lambda, EMR, and Step Functions) and Databricks (leveraging Delta Lake, Unity Catalog, and MLflow where applicable).

The Senior Data Engineer will architect and implement dynamic reporting, analytics, and data modeling solutions that drive measurable outcomes in the education domain, while ensuring the performance, efficiency, and reliability of the broader Data Platform. The ideal candidate brings a strong data engineering foundation with deep, hands‑on expertise in AWS cloud infrastructure and Databricks, including experience with Delta Lake architecture, medallion (Bronze/Silver/Gold) data design patterns, and Databricks Workflows for pipeline orchestration.

Advanced proficiency in SQL and experience with Python or Scala for large‑scale data transformation are essential. Familiarity with infrastructure-as-code (e.g., Terraform) and CI/CD practices for data pipelines is a strong plus.

This role requires close collaboration with business stakeholders, data analysts, and product teams to translate complex data requirements into robust, production‑grade engineering solutions â ensuring timely, high‑quality delivery across all data initiatives.

This is aremote position open to applicants authorized to work for any employer within the United States.

• Senior Data Engineer must have prior hands‑on experience designing and delivering data solutions on Databricks, including building and maintaining lake houses using Delta Lake with a medallion (Bronze/Silver/Gold) architecture.
• Strong knowledge working with data from financial and operational systems, with proven experience implementing Slowly Changing Dimensions (SCD Types 1, 2, and
  3) using Delta Lake MERGE operations and Databricks SQL within a unified lakehouse model.
• Experience running and optimizing cloud data platforms on Databricks, including cluster configuration, autoscaling policies, job scheduling via Databricks Workflows, and adherence to daily runbook SLAs through proactive monitoring and alerting.
• Strong experience with Git‑based version control integrated into Databricks (Databricks Repos / Git folders) and project management tools such as Jira, operating within Agile/Kanban delivery frameworks.
• Strong experience with modern data architecture principles, including Unity Catalog for data governance, Delta Sharing, and cloud‑native lakehouse design patterns on AWS with Databricks.
• Ability to translate business requirements into technical designs and deliver production‑grade data solutions within Databricks, from initial scoping through deployment.
• Design and develop parallel and distributed ETL/ELT pipelines using Apache Spark (PySpark/Scala) on Databricks, applying partitioning, caching, and broadcast join strategies for optimal resource efficiency and throughput.
• Understand data mapping and transformation requirements and implement them…