Data Engineer

Trane Italia•Saint Paul, MN

10d•$91,517 - $128,380•Hybrid

About The Position

A sustainable future demands ongoing digital advancement. Our digital solutions team leads the way in developing next-generation climate technology focused on reducing demand-side energy consumption and emissions. Our team—including BrainBox AI, Nuvolo, and more—combines technical expertise with advanced analytics to create data-driven solutions that add real value for customers, communities, and the planet. Whether you're advancing AI in HVAC or driving analytics for greater efficiency, your ideas will help engineer solutions for stronger communities and a sustainable world. Trane Technologies is seeking an experienced Data Engineer who will be responsible for managing and optimizing our database systems, with a special emphasis on NoSQL databases, cloud-native architectures, and high-volume data processing. The role involves designing scalable, distributed data solutions, writing Python scripts to migrate/build data across different applications and systems, and working with both SQL and NoSQL technologies in cloud-native environments. The position works closely with product, design, and development teams to review requirements, evaluate data models, and build database structures optimized for scale and performance. This includes designing, implementing, and maintaining architectures and cloud-native data platforms to ensure high performance, availability, and security while processing terabytes to petabytes of data.

Requirements

Bachelor of Science degree in Computer Science, Computer Engineering, or equivalent required.
6+ years of experience in Database Engineer, Data Engineer, or similar role with strong NoSQL expertise.
Deep hands-on experience with NoSQL databases (DynamoDB, BigQuery, BigTable, or similar).
Strong understanding of CAP theorem, eventual consistency, and distributed system concepts.
Experience designing denormalized data models and optimizing for read/write patterns in NoSQL databases.
Hands-on experience with big data and in cloud-native technologies.
Experience in writing Python scripts for data migration, governance, validation.
Experience in maintaining high-performance SQL and NoSQL databases at scale.
Good understanding of AWS and GCP systems, particularly managed NoSQL services and cloud-native data platforms.
Experience in migrating data from different systems, including legacy relational databases to NoSQL platforms and on-prem to cloud migrations.
Knowledge of data lake architectures and modern data stack tools.
Experience with data governance, data quality frameworks, and metadata management.
Understanding of MLOps and data engineering best practices for machine learning pipelines.
Excellent analytical and problem-solving skills.
Strong communication skills, ability to document complex data architectures and patterns.

Nice To Haves

Relevant certifications are highly desirable: AWS Certified Data Analytics Specialty or AWS Certified Database Specialty.
Google Cloud Professional Data Engineer.
DataBricks Certified Data Engineer.
Or similar.

Responsibilities

Design, implement, and maintain both SQL and NoSQL database systems to ensure high performance, availability, and security.
Architect and deploy cloud-native database solutions using serverless technologies.
Conduct data analysis to support business decisions and optimize NoSQL data models and query patterns.
Develop, implement, and optimize SQL queries and NoSQL data access patterns for various database engines.
Design and implement real-time and batch data processing pipelines for high-volume data streams.
Analyze, evaluate data and design schema-less and flexible data models suited for NoSQL databases.
Build dashboards through reporting tools that integrate data from multiple NoSQL and SQL sources.
Manage the migration of data across systems, including relational to NoSQL database migrations and cloud migrations.
Utilize cloud services for NoSQL database management, operations, and scaling (AWS DynamoDB, BigQuery, Bigtable, etc.).
Design and implement data partitioning, sharding, and replication strategies for high-volume NoSQL databases.
Monitor and optimize database performance, including NoSQL index tuning, query optimization, and capacity planning for high-throughput systems.
Implement data lake and data mesh architectures for scalable data storage and analytics.
Design streaming data architectures for real-time analytics and event-driven systems.
Collaborate with development teams to ensure data consistency, integrity, and correctness across polyglot persistence layers.
Ensure database security and compliance with relevant regulations across SQL and NoSQL platforms.
Provide support for data-related issues and troubleshoot complex distributed NoSQL database issues as needed.
Implement CI/CD pipelines for database schema migrations and data pipeline deployments.
HVAC domain knowledge is an additional advantage, providing insights for domain-specific requirements and optimizations.