Senior Application Data Architect - GP, Remote: Colombia - Costa Rica, Fulltime.

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    "description": "<p><span style=\"font-size: 14pt; font-weight: bold\">- This position is open to candidates located in Colombia or Costa Rica only -</span></p>\n<p><br><br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Application Data Architect </span></p>\n<p><br></p>\n<p>This hybrid role combines technical architecture leadership (50%) and hands-on data engineering (50%). You will lead the design and evolution of enterprise data platforms while actively contributing to delivery.</p>\n<p>You’ll collaborate with Enterprise Architecture, Data Architecture, Product Owners, and cross-functional engineering teams to translate strategy into scalable, production-ready solutions.</p>\n<p>This role expands beyond execution, driving technical direction, standards, and system-level thinking across multiple initiatives.</p>\n<p><br></p>\n<p><span style=\"text-decoration: underline\"><span style=\"font-weight: bold\">Key Responsibilities</span></span><br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">1. Architecture &amp; Technical Leadership</span><br></p>\n<p><br></p>\n<ul>\n<li>Design and evolve enterprise data architectures, including Lakehouse, Data Warehouse, pipelines, semantic models, and reporting layers.</li>\n<li>Define and maintain architectural standards, patterns, and best practices across Microsoft Fabric and Azure services.</li>\n<li>Translate enterprise data strategy into epics, features, and actionable technical stories.</li>\n<li>Lead technical planning activities, identifying dependencies, risks, and trade-offs early in the lifecycle.</li>\n<li>Establish and enforce standards for data quality, taxonomy, pipeline design, and semantic modeling.</li>\n<li>Review solution designs and critical implementations to ensure scalability, performance, and maintainability.</li>\n<li>Act as a technical leader and mentor, elevating engineering practices and system-level thinking.</li>\n<li>Serve as a technical integrator across Data Engineers, Data Scientists, and Architects<br></li>\n</ul>\n<p><br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">2. Data Engineering &amp; Delivery</span></p>\n<p><br></p>\n<ul>\n<li>Design, build, and enhance data pipelines, dataflows, notebooks, and semantic models.</li>\n<li>Contribute hands-on to complex and high-impact initiatives where architecture and implementation intersect.</li>\n<li>Support platform modernization, including migration from on-prem SQL Server to Microsoft Fabric.</li>\n<li>Optimize data solutions for performance, reliability, and cost efficiency.</li>\n<li>Collaborate with Data Scientists to productionize ML models and integrate them into enterprise pipelines.</li>\n<li>Apply AI-assisted techniques to improve development workflows and solution quality.</li>\n<li>Deliver scalable, maintainable, and high-quality data solutions aligned with best practices.</li>\n</ul>\n<p><br></p>\n<p><br><span style=\"font-weight: bold\">3. Operational Excellence &amp; Collaboration</span></p>\n<p><br></p>\n<ul>\n<li>Participate in cross-project planning and release activities.</li>\n<li>Collaborate with Product Owners and stakeholders to align solutions with business needs and priorities.</li>\n<li>Monitor systems using logs and dashboards to ensure performance, reliability, and issue resolution.</li>\n<li>Create and maintain clear, concise technical documentation (architecture, systems, processes).</li>\n<li>Contribute to a collaborative, inclusive, and team-first engineering culture.<br></li>\n</ul>\n<p><br></p>\n<p><span style=\"text-decoration: underline\"><span style=\"font-weight: bold\">Requirements</span></span></p>\n<p><br><span style=\"font-weight: bold\">Technical &amp; Data Engineering Expertise</span></p>\n<ul>\n<li>4+ years of experience in software/data engineering (Python, PySpark, Spark or similar).</li>\n<li>Strong experience designing and building enterprise data platforms (Lakehouse, Data Warehouse, Analytics).</li>\n<li>SQL, relational databases, and large-scale data systems</li>\n<li>Data pipelines, ETL/ELT processes, and query optimization</li>\n<li>Semantic modeling and reporting tools (e.g., Power BI)</li>\n<li>Experience with cloud data platforms (preferably Azure / Microsoft Fabric or similar).</li>\n<li>Familiarity with distributed data technologies (e.g., Spark, Kafka, Hadoop or cloud-native equivalents).</li>\n<li>Understanding of CI/CD, DataOps/MLOps, and modern deployment practices.</li>\n<li>Experience working with APIs and system integrations.</li>\n</ul>\n<p><br></p>\n<p><br><span style=\"font-weight: bold\">Architecture &amp; Delivery</span></p>\n<ul>\n<li>Proven ability to translate architectural strategy into scalable, production-ready solutions.</li>\n<li>Experience partnering with Enterprise and Data Architects to deliver aligned solutions.</li>\n<li>Strong understanding of data modeling, taxonomy, and data quality practices.</li>\n<li>Ability to balance hands-on development with technical leadership responsibilities.</li>\n<li>Experience contributing to technical design, planning, and estimation in Agile environments.</li>\n</ul>\n<p><br><span style=\"font-weight: bold\">AI / ML (Preferred)</span></p>\n<p><br></p>\n<ul>\n<li>Experience with ML frameworks (e.g., scikit-learn, TensorFlow, Azure ML) is a plus.</li>\n<li>Exposure to integrating ML models into production data pipelines.</li>\n<li>Interest or experience in applying AI/automation to improve engineering workflows and solution quality.</li>\n</ul>\n<p><br></p>\n<p><br><span style=\"font-weight: bold\">Professional Skills</span></p>\n<p><br></p>\n<ul>\n<li>Strong communication skills with the ability to explain complex concepts to technical and non-technical stakeholders.</li>\n<li>Experience working in Agile/Scrum teams with Product Owners and cross-functional roles.</li>\n<li>Self-motivated, proactive, and comfortable operating with ambiguity and ownership.</li>\n<li>Strong attention to code quality, testing, and maintainability.</li>\n<li>Collaborative mindset with a focus on team success and knowledge sharing.</li>\n<li>Bachelor’s degree in Computer Science or related field (or equivalent experience).</li>\n</ul>",
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