Senior Engineer - Data Engineering

McGraw Hill LLC. • Columbus, OH

1d

About The Position

McGraw Hill is hiring a Senior Engineer for its Insights and Personalization Engineering team to build reporting and personalization features at scale on the Open Learning platform. The role focuses on data engineering in Databricks for Symphony, the platform behind teacher- and administrator-facing reports for products including PRoPL, OpenLearning, and MHPlus.

The engineer will own Databricks lakehouse data pipelines and analytics models that power reports used by millions of users, from data ingestion through the serving layer consumed by reporting APIs and user interfaces. The role works closely with backend, UI, product, and data platform teams to shape how McGraw Hill delivers insights to educators.

Responsibilities include translating business requirements into technical specifications and solution designs; building and maintaining scalable batch and incremental pipelines; designing reporting models; optimizing the SQL serving layer, Spark and SQL performance, and compute costs; and ensuring data quality, observability, reliability, governance, and access controls. The engineer will also lead design reviews and mentor other engineers.

The technology stack includes Go, Python/PySpark, Spark SQL, Scala, Databricks and Delta Lake, Unity Catalog, AWS services and data stores, GitHub, GitHub Actions, Docker, Kubernetes, ECS, EKS, Terraform, Jira, Confluence, and Slack.

Requirements

• At least 5 years of software or data engineering experience, including at least 3 years building production data pipelines on Databricks or an equivalent Spark platform in AWS.
• Experience delivering production-grade, fault-tolerant software in a fast-paced environment with a distributed team.
• Advanced SQL skills, including tuning complex analytical queries over large datasets.
• Expertise in data warehousing, lakehouse concepts, data modeling, and cloud data architecture.
• Strong applied knowledge of several of the following: Unity Catalog governance, batch and incremental ETL/ELT, Spark performance tuning, REST services, AWS data services (Athena, Glue, EMR, Lambda), Terraform, GitHub Actions, and Git.
• Bachelor’s degree in Computer Science or a related field, or equivalent experience.

Nice To Haves

• Education or publishing domain experience.
• Streaming/CDC ingestion, such as Kafka, into Delta Lake.
• Experience with data quality frameworks such as Delta Live Tables or Great Expectations.
• Databricks certification.

Responsibilities

• Translate business requirements into technical specifications and solution designs in partnership with product and engineering leaders.
• Build and maintain scalable batch and incremental data pipelines using PySpark, Spark SQL, Delta Lake, and Databricks Workflows.
• Design reporting data models using dimensional modeling and medallion (bronze/silver/gold) architecture.
• Build and optimize the SQL serving layer in Unity Catalog, including views, materialized views, and table-valued functions.
• Tune Spark and SQL performance and manage compute costs.
• Own data quality, observability, and reliability through automation, testing, and monitoring.
• Apply data governance and access controls through Unity Catalog.
• Lead design reviews and mentor engineers on data engineering best practices.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior