Job description Yellowstone Local is proud to represent MRCOOL, an industry leader in HVAC.If you know how to turn fragmented systems into one trusted source of truth, this is your chance to build the data foundation of a fast-growing HVAC brand from the ground up.

What's in it for You?

High-visibility, high-ownership role with direct impact on company-wide decision-makingOpportunity to architect and build a greenfield enterprise data warehouse on Google BigQuery and Google CloudLead the consolidation of data across ERP, accounting, CRM, e-commerce, EDI, support, telephony, and analytics platformsPartner directly with finance and operations leadership on business-critical KPIs, dashboards, and executive scorecardsWork with modern data engineering, AI-assisted development, and natural-language analytics toolsShape MRCOOL's data governance, semantic layer, business dictionary, and enterprise reporting standardsBuild the foundation for AI-driven access to trusted business dataCompensation, schedule, and additional benefits Why You'll Love It HereYou will not inherit a finished system and simply maintain it. You will design the architecture, standards, and workflows that define how MRCOOL uses data going forward.

Your work will solve a meaningful business challenge by bringing more than a dozen disconnected platforms into a governed, decision-ready data environment.

You will have ownership over warehouse architecture, ELT pipelines, historical data cleanup, governance, data quality, reporting, and AI enablement.

You will work closely with business leaders instead of operating in a silo, giving you direct visibility into how your engineering decisions affect finance, operations, supply chain, and growth.

MRCOOL is a fast-growing HVAC technology company focused on innovative, energy-efficient ductless mini splits and ducted central air solutions.

You will have the opportunity to apply modern Google Cloud, BigQuery, BI, data engineering, and generative AI technologies at enterprise scale.

Your New RoleServe as the Senior Data Engineer responsible for architecting, building, and governing MRCOOL's enterprise data warehouse on Google BigQuery and Google CloudDesign a modern ELT architecture using raw, staging, conformed core, and department-level data martsBuild scalable, production-grade ETL and ELT pipelines that ingest and transform data from NetSuite, Sage Intacct, QuickBooks, HubSpot, Magento, Zendesk, Aircall, Google Analytics, Google Drive, and additional business systemsIntegrate EDI, 3PL, and trading-partner data flows from platforms including Celigo, SPS Commerce, CommerceHub, Logicbroker, and qStockOptimize BigQuery performance and cost through partitioning, clustering, storage strategies, materialized views, workload management, slot reservations, editions, and consumption monitoringEstablish enterprise data governance practices covering ownership, role-based access, lineage, PII handling, metadata, and data qualityCreate and maintain a shared business data dictionary and semantic or metrics layer so core terms such as revenue, margin, fill rate, and DSO have consistent definitionsReconcile multiple systems of record into unified financial structures, conformed dimensions, and a consistent chart of accountsAssess, clean, deduplicate, validate, and consolidate years of historical data from legacy systems, databases, and spreadsheetsDefine automated data quality rules, reconciliation processes, and validation controls that improve trust in reportingPartner with finance and operations leaders to define KPIs and deliver governed dashboards and executive scorecards, beginning with FinanceBuild reporting solutions using modern business intelligence platforms such as Power BI, Looker, Looker Studio, Tableau, or similar toolsCreate the governed data and semantic foundation required for natural-language querying and AI-powered analytics using tools such as Gemini in BigQuery, Conversational Analytics Agent/API, or comparable technologiesUse modern data engineering and AI-assisted development tools to improve testing, documentation, pipeline reliability, metadata management, and developer productivityWork with Google Cloud technologies including BigQuery, Google Cloud Storage, Dataflow, Dataproc, Cloud Data Fusion, Datastream, BigQuery Data Transfer Service, Dataplex, Cloud Functions, Cloud Run, Pub/Sub, and related servicesJob location: City and state were not provided in the intake

Hiring Expectations:

Apply today, complete a quick phone screening, and get ready for an interview with our team to discuss your goals and experience.10+ years of hands-on data engineering experience within a major public cloud environmentGoogle Cloud Platform experience required7+ years of hands-on experience designing, deploying, integrating, and operating Google BigQuery as an enterprise data warehouseAdvanced SQL skills and strong experience with dimensional modeling, conformed data models, and enterprise warehouse designStrong experience with Google Cloud Storage for data lake storage, staging, retention, and lifecycle managementExperience building pipelines with Google Cloud data services such as Dataflow, Dataproc, Cloud Data Fusion, Datastream, or BigQuery Data Transfer ServiceExperience with metadata management and data cataloging using Dataplex, Knowledge Catalog, or comparable technologiesExperience using Cloud Functions, Cloud Run, and Pub/Sub for event-driven data processing and pipeline automationStrong EDI experience, including trading-partner and 3PL data integrationProven ability to build reliable, scalable, production-grade ETL and ELT pipelinesStrong experience with data governance, data quality, data lineage, access controls, and business or metric definitionsDemonstrated success cleaning, deduplicating, reconciling, and consolidating historical data from disparate legacy systemsExperience developing KPIs, dashboards, executive scorecards, and business intelligence solutions using Power BI, Looker, Tableau, Looker Studio, or similar platformsExperience with modern data and AI tooling, including AI-assisted development, natural-language-to-SQL, generative AI, or LLM-based analyticsStrong communication skills with the ability to work directly with finance, operations, and other business stakeholdersExperience integrating NetSuite, Sage Intacct, or QuickBooks data preferredExperience with dbt or comparable SQL transformation frameworks preferredExperience with Airbyte, Fivetran, or similar EL tools preferredExperience with Cloud Composer, Apache Airflow, Dataform, or similar orchestration tools preferredGoogle Cloud Professional Data Engineer certification preferredExperience in distribution, wholesale, manufacturing, or supply-chain environments preferredFamiliarity with Magento, HubSpot, Zendesk, and Aircall data preferredBachelor's degree in Computer Science, Information Systems, or a related field preferredMRCOOL is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, gender, gender identity, sexual orientation, national origin, genetics, disability, age, or veteran status.#green