Senior Application Data Architect

Gorilla Logic

Senior Application Data Architect leading enterprise data architecture and engineering initiatives. Collaborating with cross-functional teams to design and build scalable data solutions.

Posted 4/11/2026full-timeRemote • 🇨🇴 ColombiaSeniorWebsite

Tech Stack

Tools & technologies

AzureCloudETLHadoopKafkaPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Design and evolve enterprise data architectures, including Lakehouse, Data Warehouse, pipelines, semantic models, and reporting layers.
Define and maintain architectural standards, patterns, and best practices across Microsoft Fabric and Azure services.
Translate enterprise data strategy into epics, features, and actionable technical stories.
Lead technical planning activities, identifying dependencies, risks, and trade-offs early in the lifecycle.
Establish and enforce standards for data quality, taxonomy, pipeline design, and semantic modeling.
Review solution designs and critical implementations to ensure scalability, performance, and maintainability.
Act as a technical leader and mentor, elevating engineering practices and system-level thinking.
Design, build, and enhance data pipelines, dataflows, notebooks, and semantic models.
Contribute hands-on to complex and high-impact initiatives where architecture and implementation intersect.
Support platform modernization, including migration from on-prem SQL Server to Microsoft Fabric.
Optimize data solutions for performance, reliability, and cost efficiency.
Collaborate with Data Scientists to productionize ML models and integrate them into enterprise pipelines.
Apply AI-assisted techniques to improve development workflows and solution quality.
Deliver scalable, maintainable, and high-quality data solutions aligned with best practices.
Participate in cross-project planning and release activities.
Collaborate with Product Owners and stakeholders to align solutions with business needs and priorities.
Monitor systems using logs and dashboards to ensure performance, reliability, and issue resolution.
Create and maintain clear, concise technical documentation (architecture, systems, processes).

Requirements

What you’ll need

4+ years of experience in software/data engineering (Python, PySpark, Spark or similar)
Strong experience designing and building enterprise data platforms (Lakehouse, Data Warehouse, Analytics)
SQL, relational databases, and large-scale data systems
Data pipelines, ETL/ELT processes, and query optimization
Semantic modeling and reporting tools (e.g., Power BI)
Experience with cloud data platforms (preferably Azure / Microsoft Fabric or similar)
Familiarity with distributed data technologies (e.g., Spark, Kafka, Hadoop or cloud-native equivalents)
Understanding of CI/CD, DataOps/MLOps, and modern deployment practices
Experience working with APIs and system integrations.
Bachelor’s degree in Computer Science or related field (or equivalent experience)

Benefits

Comp & perks

Health insurance
401(k)
Flexible work arrangements
Professional development

ATS Keywords

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Hard Skills & Tools

PythonPySparkSparkSQLETLELTsemantic modelingdata pipelinesquery optimizationdata architecture

Soft Skills

technical leadershipmentoringcollaborationcommunicationplanningproblem-solvingdocumentation

Certifications

Bachelor’s degree in Computer Science