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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 environmentsDefine and drive engineering standards and design patternsInfluence technical direction across teamsMentor and elevate other engineersBalance short-term delivery with long-term platform healthThis 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 MattersYou 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 adecuado 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 enterprisEssential Duties and Responsibilities:Design, build, and operate scalable,



production-grade data products with a focus on usability, discoverability, and alignment with business outcomesOwn core data platform architecture, including data pipelines, storage, and foundational data models within DatabricksArchitect, 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 improvementDesign and operate data solutions that handle large-scale, high-volume, and complex data workloads with a focus on reliability and performanceMaintain a strong hands-on focus, actively contributing to the design, development, and operation of data solutions in production environmentsLead technical decision-making for complex data engineering initiatives, taking ownership of design choices and their long-term impact on the platformCollaborate with data visualization and analytics engineers to ensure appropriate placement of data transformations, business logic, and aggregationsCollaborate across engineering roles to ensure end-to-end data quality, consistency, and reliabilityLeverage AI-based tools and techniques to accelerate delivery and improve engineering productivityDesign, build, and operate data quality, validation, and observability frameworksDesign and implement testing strategies for data pipelinesOptimize data pipelines and platform usage for performance, scalability, and cost efficiencyDiagnose and resolve complex data pipeline failuresEnsure data assets are discoverable and well-documentedImplement secure data access patterns and governanceEnsure compliance with data governance and regulatory requirementsCollaborate with cross-functional teams to translate requirements into scalable data solutionsMentor engineers and contribute to a high-performance, collaborative engineering cultureContribute to the evolution of the data platform to improve scalability, usability,



and engineering efficiencyStay current with advancements in data engineering and DatabricksQualifications: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 AbilitiesDeep, hands-on experience designing, building, and optimizing data pipelines and data products within Azure Databricks environmentsDatabricks must be the primary platform used in recent roles, not incidental or secondary experienceProven experience optimizing Databricks workloads and overall platform usage for performance, scalability, and cost efficiencyStrong proficiency in PySpark and Spark within Databricks, including performance tuningStrong understanding of Medallion Architecture implemented within DatabricksExperience building and operating production-grade pipelines within DatabricksExperience with Databricks-native ingestion frameworksExperience implementing CI/CD pipelines within DatabricksStrong troubleshooting skills in distributed systems, Strong communication skillsDemonstrated ability to evaluate and make sound tradeoffs across performance, scalability, cost, maintainability, and time-to-deliveryPreferred Knowledge, Skills, and AbilitiesExperience with Databricks GenieExperience with AI-assisted data engineering toolsExperience with enterprise data platformsExperience collaborating with BI teamsKnowledge of governance and securityFamiliarity with Infrastructure as Code, Relevant cloud certificationsAzure DevOps experience for work trackingSuccess Traits for this RoleStrong ownership mindset with accountability for end-to-end delivery and productionreliabilityAbility to evaluate tradeoffs across performance, scalability, and maintainabilityAbility to make high-quality decisions in ambiguous environmentsExcellent communication and collaboration skillsStrong bias toward execution and deliveryCommitment to continuous improvement and operational excellenceExperience with incident response and root cause analysisHigh learning agility and adaptabilityCommitment to building and supporting resilient data systems across team boundariesSet and uphold a high bar for code quality, performance, and reliability
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📌 Data Engineer (Monterrey)
🏢 Daikin Manufacturing México
📍 Monterrey