Make your mark at the world's largest HVAC company! Summary: Daikin Applied Americas is seeking a Senior Data Engineer with deep, hands-on expertise in Azure Databricks as a primary data engineering platform to design, build, and operate scalable, production-grade data pipelines and data products. This role is responsible for ensuring the availability, reliability, and quality of data across the organization. This role operates as part of a unified data platform team, working in close alignment with data visualization engineers, analytics teams, and data product owners to deliver cohesive, scalable, and high-quality data products. You will collaborate with cross-functional teams to deliver data solutions that power analytics, business intelligence, machine learning, and emerging AI-driven experiences leveraging Databricks capabilities such as Genie and related AI-assisted tooling. This role requires strong ownership, a design-first mindset, and a bias toward delivering reliable, production-ready data solutions in complex environments. This is a high-impact, high-expectation role requiring deep technical expertise in Databricks and a proven ability to deliver production-grade data solutions at scale. We are seeking engineers who operate at a high level of ownership, consistently deliver high-quality work, and contribute to raising the bar for engineering excellence across the team. This role operates at a senior level and requires the ability to: · Make and own architectural decisions in ambiguous environments · Define and drive engineering standards and design patterns · Influence technical direction across teams · Mentor and elevate other engineers · Balance short-term delivery with long-term platform health This role emphasizes production excellence, requiring ownership of reliability, observability, and continuous improvement of data systems at scale, as well as defining and enforcing strong design patterns. Why This Role Matters You will play a critical role in shaping the organization’s data platform and enabling data-driven decision-making. Your work will directly impact how data is trusted, accessed, and used across the enterprise. This role is ideal for an engineer who thrives on hands-on ownership, sets a high bar for engineering excellence, and is driven to design, build, and operate robust, scalable data systems that deliver meaningful impact across the enterpris Essential Duties and Responsibilities: Design, build, and operate scalable, production-grade data products with a focus on usability, discoverability, and alignment with business outcomes Own core data platform architecture, including data pipelines, storage, and foundational data models within Databricks Architect, implement, and continuously evolve data models and curation patterns (e.g., Medallion Architecture) Own data solutions end-to-end in production, including design, development, deployment, monitoring, incident response, root cause analysis, and continuous improvement Design and operate data solutions that handle large-scale, high-volume, and complex data workloads with a focus on reliability and performance Maintain a strong hands-on focus, actively contributing to the design, development, and operation of data solutions in production environments Lead technical decision-making for complex data engineering initiatives, taking ownership of design choices and their long-term impact on the platform Collaborate with data visualization and analytics engineers to ensure appropriate placement of data transformations, business logic, and aggregations Collaborate across engineering roles to ensure end-to-end data quality, consistency, and reliability Leverage AI-based tools and techniques to accelerate delivery and improve engineering productivity Design, build, and operate data quality, validation, and observability frameworks Design and implement testing strategies for data pipelines Optimize data pipelines and platform usage for performance, scalability, and cost efficiency Diagnose and resolve complex data pipeline failures Ensure data assets are discoverable and well-documented 16. Implement secure data access patterns and governance Ensure compliance with data governance and regulatory requirements Collaborate with cross-functional teams to translate requirements into scalable data solutions Mentor engineers and contribute to a high-performance, collaborative engineering culture Contribute to the evolution of the data platform to improve scalability, usability, and engineering efficiency Stay current with advancements in data engineering and Databricks Qualifications: Bachelor’s Degree in Computer Science, Information Systems, or a related field. 8+ years in Data Engineering and Data Architecture focused, with hands-on experience delivering solutions utilizing Databricks (preferably on Azure). Must have a strong understanding of cloud-based data solutions or equivalent combination of education and 8+ years' experience required. Required Knowledge, Skills, and Abilities Deep, hands-on experience designing, building, and optimizing data pipelines and data products within Azure Databricks environments Databricks must be the primary platform used in recent roles, not incidental or secondary experience Proven experience optimizing Databricks workloads and overall platform usage for performance, scalability, and cost efficiency Strong proficiency in PySpark and Spark within Databricks, including performance tuning Strong understanding of Medallion Architecture implemented within Databricks Experience building and operating production-grade pipelines within Databricks Experience with Databricks-native ingestion frameworks Experience implementing CI/CD pipelines within Databricks Strong troubleshooting skills in distributed systems · Strong communication skills Demonstrated ability to evaluate and make sound tradeoffs across performance, scalability, cost, maintainability, and time-to-delivery Preferred Knowledge, Skills, and Abilities Experience with Databricks Genie Experience with AI-assisted data engineering tools Experience with enterprise data platforms Experience collaborating with BI teams Experience enabling scalable data consumption Knowledge of governance and security Familiarity with Infrastructure as Code · Relevant cloud certifications Azure DevOps experience for work tracking Success Traits for this Role Strong ownership mindset with accountability for end-to-end delivery and production reliability Ability to evaluate tradeoffs across performance, scalability, and maintainability Ability to make high-quality decisions in ambiguous environments Excellent communication and collaboration skills Strong bias toward execution and delivery Commitment to continuous improvement and operational excellence Experience with incident response and root cause analysis High learning agility and adaptability Commitment to building and supporting resilient data systems across team boundaries Set and uphold a high bar for code quality, performance, and reliability