Senior Data Engineer

We are seeking a Senior Data Engineer to design, build, and maintain the core data models and transformation pipelines that power Workforce Analytics. 

This role is responsible for transforming raw, ingested data into clean, well-structured, and analytics-ready datasets in Snowflake, using Coalesce.io as the primary transformation framework. You will play a critical role in defining workforce metrics, ensuring data quality, and enabling trusted insights across HR, analytics, and business leadership. 

You will work closely with Data Integration Engineers (data ingestion) and Data Platform Engineers (data access and security) to deliver a scalable, high-quality data ecosystem. 

• Design, build, and maintain data transformation pipelines in Coalesce.io 

• Develop analytics-ready data models in Snowflake (e.g., headcount, attrition, recruiting pipelines) 

• Apply best practices for:  

• Modular, reusable transformations 

• Clear layer separation (raw → staging → curated) 

• Maintainable and scalable model design 

• Model complex Workforce / HR datasets, including:  

• Employee lifecycle (hire → transfer → termination) 

• Organizational hierarchies 

• Job and position structures 

• Recruiting pipelines 

• Handle challenges such as:  

• Implement and maintain data quality checks and validation logic 

• Ensure consistency and accuracy of key workforce metrics 

• Investigate and resolve data issues in partnership with Integration and Platform teams 

• Build trust in enterprise workforce datasets 

• Write efficient and optimized SQL for transformation pipelines 

• Improve performance of models and downstream queries 

• Design data structures that align with secure consumption patterns defined by the platform 

Partner with Data Integration Engineers to:  

• Understand source system structures (especially Workday) 

• Ensure proper ingestion and schema alignment 

Partner with Data Platform Engineers to:  

• Align on access models and consumption layers 

• Support secure and scalable data usage 

• Translate business requirements from People Analytics and HR stakeholders into data models 

• Define and standardize workforce metrics and business logic 

• Enable self-service analytics through consistent and well-documented datasets 

• Use Azure DevOps / GitHub for version control and deployment 

• Support CI/CD workflows for transformation pipelines 

• Maintain documentation for models, logic, and data definitions 

• 5+ years of experience in data engineering 

• Strong SQL skills (advanced transformations, performance tuning) 

• Hands-on experience with data transformation frameworks (Coalesce.io, dbt, or similar) 

• Experience building and maintaining analytics-ready data models 

• Experience working with cloud data platforms (Snowflake preferred) 

• Strong understanding of data modeling concepts (dimensional, SCDs, etc.) 

• Experience with Workforce / HR data (Workday strongly preferred) 

• Experience modeling effective-dated and hierarchical data 

• Exposure to People Analytics use cases and metrics 

• Familiarity with data quality frameworks and testing approaches 

• Experience working in environments with sensitive/PII data 

Johnson Controls, a global leader in thermal management, mission-critical building systems, energy efficiency, and decarbonization, helps customers use energy more productively, reduce carbon emissions, and operate with the precision and resilience required in rapidly expanding industries such as data centers, healthcare, pharmaceuticals, advanced manufacturing, and higher education.

For more than 140 years, Johnson Controls has delivered performance where it really matters. Backed by advanced technology, lifecycle services and an industry-leading field organization, we elevate customer performance, turn goals into real-world results and help move society forward.

We are committed to diversity and inclusion and believe that different perspectives make us stronger. By encouraging open dialogue and valuing individuality, we strive to be one of the most desirable places to work.

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