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# Data Architect (IR-541)

- **Company:** Intellectsoft
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Microsoft Online Services, Data Architecture, Extract Transform Load (ETL), Data Warehousing, Microsoft Data Access Components, Operational Data Store, Salesforce.Com, Technical Data Management Systems, Data Strategy, Microsoft Fabric, Marketo, Enterprise Integration, Data Lakehouse, Software Coding, Azure Data Analytics, Data Pipelines
- **Published:** July 29, 2026
- **Apply:** https://es.indeed.com/viewjob?jk=bef18571f817744f

## About the Role

* Senior Data Architecture Expertise: Extensive track record designing scalable enterprise data lakes, data warehouses, and complex ETL/ELT data pipelines from scratch.
 * Mastery of the Microsoft Data Stack: Deep, hands-on technical proficiency with the modern Microsoft ecosystem, specifically Microsoft Fabric, alongside Azure data analytics components.
 * Commercial & GTM Business Acumen: Strong familiarity with B2B enterprise sales metrics and pipelines, with the ability to turn raw commercial data into highly structured, analytics-ready models.
 * Autonomous Execution: Proven capability to work independently in an environment without pre-existing data legacy standards, delivering architectural designs alongside concrete, rapid technical implementations

## Description

* Data Lakehouse Architecture: Define the standards, blueprints, and architectural design for a brand-new, centralized data repository built from the ground up.
 * Enterprise Integration Strategy: Map out and execute the ingestion and synthesis of commercial and operational data points across critical GTM systems, including Salesforce, Marketo, Titango, and Clary.
 * Hands-on Pipeline Execution: Operates in a highly agile, "build-it-yourself" delivery model, taking full ownership of both the high-level data strategy and the hands-on coding required to construct the initial data pipelines.
 * Business Metric Synthesis: Translate complex commercial strategies into technical data models, structuring datasets to analyze win/loss records, sales pipelines, cycle velocities, and operational lead times.


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