Data Platform Developer

Data Platform DeveloperHED is hiring a Data Platform Developer to develop, evaluate, and improve the AI capabilities that support our people and our practice. About HEDWe are a team that is full of ideas, experience, creativity, passionate opinions, insatiable curiosity, uncompromising integrity, commitment, and skill. Our culture is about aspiration, embracing change and challenges, listening to (and learning from) each other, encouraging continual learning, and inspiring collective growth.

As an inclusive, integrated architecture and engineering practice, we value the diversity of perspectives, experiences, abilities, and expertise that advance both the work we do, and the world we share.

Position Summary As part of the Data & AI team, you will operate and improve a modern lakehouse built on Databricks, Delta Lake, and Unity Catalog, connecting business systems to trusted analytics and emerging AI applications.

This is an individual contributor role with meaningful ownership of production pipelines, platform health, data documentation, and continuous improvement. You will partner with analysts, application developers, and business data owners to make information accessible, dependable, and actionable. You will also help shape how AI-assisted tools are safely used to monitor and improve the platform.

Essential Functions:

• Develop, operate, and improve ingestion and transformation pipelines across Bronze, Silver, and Gold data layers, integrating sources such as Workday, Deltek, Dataverse, Microsoft Graph, and collaboration systems.
• Administer and continuously improve the Databricks environment, including workflows, compute standards, data storage, access controls, and Unity Catalog governance.
• Maintain version-controlled, reproducible platform configurations and deployment workflows; identify and resolve differences between source control and production environments.
• Implement automated data quality checks and schema contract tests to protect governed datasets from unexpected changes.
• Monitor pipeline freshness, availability, performance, and cost; maintain actionable alerts, dashboards, and operational runbooks.
• Investigate and resolve production incidents, coordinate data recovery and backfills, document root causes, and implement preventive improvements.
• Maintain technical lineage, source metadata, the data dictionary, and platform documentation; collaborate with business owners to confirm definitions and accountability.
• Assess downstream impacts of schema changes, coordinate communications with data consumers, and support controlled changes across dependent systems.
• Collaborate with analytics and AI development colleagues to deliver reliable, well-governed data products and evaluate AI-assisted operational workflows.
• Contribute to platform architecture, technical standards, and future data-source onboarding as experience and ownership expand.

Requirements
• At least 3 years of experience building and supporting production data pipelines on a cloud data platform such as Databricks, Snowflake, Microsoft Fabric/Synapse, or Big Query.
• Strong SQL and Python skills, with experience using Spark or a comparable distributed data processing framework.
• Practical experience troubleshooting production jobs, recovering or back filling data, and participating in operational incident response.
• Experience implementing monitoring, alerting, and data reliability practices.
• Ability to write clear technical documentation and communicate effectively with technical colleagues and business stakeholders.
• Preferred: experience with Delta Lake or Apache Iceberg, medallion architectures, Databricks Workflows, Unity Catalog, and Azure Data Lake Storage.
• Preferred: familiarity with infrastructure…