Senior Data Engineer

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-making Opportunity to architect and build a greenfield enterprise data warehouse on Google BigQuery and Google Cloud Lead the consolidation of data across ERP, accounting, CRM, e-commerce, EDI, support, telephony, and analytics platforms Partner directly with finance and operations leadership on business-critical KPIs, dashboards, and executive scorecards Work with modern data engineering, AI-assisted development, and natural-language analytics tools Shape MRCOOL’s data governance, semantic layer, business dictionary, and enterprise reporting standards Build the foundation for AI-driven access to trusted business data Compensation, schedule, and additional benefits were not specified in the intake Why You’ll Love It Here You 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 Role Serve as the Senior Data Engineer responsible for architecting, building, and governing MRCOOL’s enterprise data warehouse on Google BigQuery and Google Cloud Design a modern ELT architecture using raw, staging, conformed core, and department-level data marts Build 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 systems Integrate EDI, 3PL, and trading-partner data flows from platforms including Celigo, SPS Commerce, CommerceHub, Logicbroker, and qStock Optimize BigQuery performance and cost through partitioning, clustering, storage strategies, materialized views, workload management, slot reservations, editions, and consumption monitoring Establish enterprise data governance practices covering ownership, role-based access, lineage, PII handling, metadata, and data quality Create 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 definitions Reconcile multiple systems of record into unified financial structures, conformed dimensions, and a consistent chart of accounts Assess, clean, deduplicate, validate, and consolidate years of historical data from legacy systems, databases, and spreadsheets Define automated data quality rules, reconciliation processes, and validation controls that improve trust in reporting Partner with finance and operations leaders to define KPIs and deliver governed dashboards and executive scorecards, beginning with Finance Build reporting solutions using modern business intelligence platforms such as Power BI, Looker, Looker Studio, Tableau, or similar tools Create 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 technologies Use modern data engineering and AI-assisted development tools to improve testing, documentation, pipeline reliability, metadata management, and developer productivity Work 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 services Job 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 environment Google Cloud Platform experience required 7+ years of hands-on experience designing, deploying, integrating, and operating Google BigQuery as an enterprise data warehouse Advanced SQL skills and strong experience with dimensional modeling, conformed data models, and enterprise warehouse design Strong experience with Google Cloud Storage for data lake storage, staging, retention, and lifecycle management Experience building pipelines with Google Cloud data services such as Dataflow, Dataproc, Cloud Data Fusion, Datastream, or BigQuery Data Transfer Service Experience with metadata management and data cataloging using Dataplex, Knowledge Catalog, or comparable technologies Experience using Cloud Functions, Cloud Run, and Pub/Sub for event-driven data processing and pipeline automation Strong EDI experience, including trading-partner and 3PL data integration Proven ability to build reliable, scalable, production-grade ETL and ELT pipelines Strong experience with data governance, data quality, data lineage, access controls, and business or metric definitions Demonstrated success cleaning, deduplicating, reconciling, and consolidating historical data from disparate legacy systems Experience developing KPIs, dashboards, executive scorecards, and business intelligence solutions using Power BI, Looker, Tableau, Looker Studio, or similar platforms Experience with modern data and AI tooling, including AI-assisted development, natural-language-to-SQL, generative AI, or LLM-based analytics Strong communication skills with the ability to work directly with finance, operations, and other business stakeholders Experience integrating NetSuite, Sage Intacct, or QuickBooks data preferred Experience with dbt or comparable SQL transformation frameworks preferred Experience with Airbyte, Fivetran, or similar EL tools preferred Experience with Cloud Composer, Apache Airflow, Dataform, or similar orchestration tools preferred Google Cloud Professional Data Engineer certification preferred Experience in distribution, wholesale, manufacturing, or supply-chain environments preferred Familiarity with Magento, HubSpot, Zendesk, and Aircall data preferred Bachelor’s degree in Computer Science, Information Systems, or a related field preferred MRCOOL 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