Senior Data Engineer

• Design, develop, and maintain scalable and reliable data pipelines using Python, SQL, Airflow, dbt, Spark, and cloud-native technologies. 

• Develop reusable, maintainable, and version-controlled data models that support operational reporting, analytics, and advanced use cases. 

• Optimize Snowflake data structures, workloads, and SQL performance to improve scalability and cost efficiency. 

• Implement automated data validation, testing, monitoring, and observability frameworks to ensure high data quality and data reliability. 

• Develop data products and semantic data layers that enable self-service analytics and standardized business metrics. 

Cloud Data Platform & Integration 

• Design integrations between Snowflake, enterprise applications, APIs, cloud storage platforms, and operational systems. 

• Build and support data ingestion frameworks utilizing REST APIs, file-based integrations, and event-driven architectures. 

• Leverage Git-based version control and software engineering practices to improve maintainability and reliability of data assets. 

Architecture & Technical Leadership 

• Provide technical leadership on data modeling, pipeline design, orchestration, and platform scalability. 

• Establish standards for documentation, testing, monitoring, and operational support. 

• Mentor junior engineers and promote engineering excellence across the data organization. 

• Drive continuous improvement initiatives focused on platform modernization, automation, and operational efficiency. 

Business Partnership & Collaboration 

• Collaborate with stakeholders across Supply Chain, Service Planning, Manufacturing, Operations, and Analytics organizations to translate business requirements into scalable data solutions. 

• Partner with Data Science, BI, and Enterprise Analytics teams to deliver trusted and governed datasets. 

• Support data-driven decision making through development of reliable, high-quality data products and analytical frameworks. 

Operational Expectations 

• Maintain overlapping working hours with EST mornings to support collaboration with global teams and stakeholders. 

• Participate in production support, root-cause analysis, and incident resolution for critical data pipelines and platforms. 

• Contribute to on-call support and operational excellence activities as needed.