Data Architect
Description
🚀 We’re Hiring: Data Architect
📍 Bogotá, Colombia | Hybrid
📍 Bogotá, Colombia | Hybrid
Who We Are
Our Bogotá tech hub works closely with teams across North America, Europe, and Asia to evolve our Freight Operating System, enabling smarter, faster, and more reliable logistics operations.
We foster a fast-paced, inclusive environment where innovation, ownership, and problem-solving thrive—and where data plays a critical role in shaping the future of logistics.
🔍 Job Summary
We are seeking a Data Architect to define, stabilize, and evolve our enterprise data architecture across legacy platforms and next-generation cloud systems.
This is a strategic and hands-on role, responsible for designing scalable and well-governed data models, leading modernization initiatives, supporting production stabilization, and enabling analytics, AI, and vector-based workloads.
This is a strategic and hands-on role, responsible for designing scalable and well-governed data models, leading modernization initiatives, supporting production stabilization, and enabling analytics, AI, and vector-based workloads.
You will serve as the technical authority for data architecture, working closely with data engineers, DBAs, BI teams, and IT to ensure data integrity, performance, observability, and long-term sustainability across Cortex and related platforms.
🧩 Core Responsibilities
1. Data Strategy & Architecture
• Define enterprise-level data architecture for Cortex and related platforms.
• Design scalable, secure, and well-governed schemas, evolving from MVP designs to long-term maintainable models.
• Own and enforce data modeling standards across the organization.
• Guide the evolution of hybrid on-prem and cloud data platforms.
• Act as the architectural authority for data design (not a purely operational role).
• Design scalable, secure, and well-governed schemas, evolving from MVP designs to long-term maintainable models.
• Own and enforce data modeling standards across the organization.
• Guide the evolution of hybrid on-prem and cloud data platforms.
• Act as the architectural authority for data design (not a purely operational role).
2. Data Modeling
• Lead hands-on data modeling, including:
– Relational and non-relational modeling
– Dimensional modeling (star / snowflake)
– Data Vault modeling (DBT + Data Vault patterns)
• Modernize legacy data models into cloud-ready architectures.
• Align models with domain-driven design in collaboration with Solution Architects.
– Relational and non-relational modeling
– Dimensional modeling (star / snowflake)
– Data Vault modeling (DBT + Data Vault patterns)
• Modernize legacy data models into cloud-ready architectures.
• Align models with domain-driven design in collaboration with Solution Architects.
3. Platform Stabilization (Short–Medium Term)
• Support and improve existing production data platforms—not only greenfield initiatives.
• Provide architectural guidance to reduce:
– Production failures
– Duplicate records
– Data merge anomalies
• Partner closely with production support and data engineering teams while maintaining a long-term architectural vision.
• Provide architectural guidance to reduce:
– Production failures
– Duplicate records
– Data merge anomalies
• Partner closely with production support and data engineering teams while maintaining a long-term architectural vision.
4. Data Pipelines & ETL
• Design and oversee reliable, observable, and governed ETL / ELT pipelines.
• Lead migration from legacy SSIS pipelines to modern frameworks.
• Hands-on experience with:
– DBT
– Batch and incremental pipelines
• Integrate multiple data sources, including TMS, CargoWise, finance systems, collaboration telemetry, and external operational feeds.
• Support CI/CD for data pipelines using Azure DevOps.
• Lead migration from legacy SSIS pipelines to modern frameworks.
• Hands-on experience with:
– DBT
– Batch and incremental pipelines
• Integrate multiple data sources, including TMS, CargoWise, finance systems, collaboration telemetry, and external operational feeds.
• Support CI/CD for data pipelines using Azure DevOps.
đź› Technologies & Platforms
Core & Hybrid Platforms
• Microsoft SQL Server (2019): SSMS, SSIS, SSRS
• Hybrid architectures integrating on-prem SQL Server with cloud platforms
• Microsoft SQL Server (2019): SSMS, SSIS, SSRS
• Hybrid architectures integrating on-prem SQL Server with cloud platforms
Cloud & Azure Stack
• Microsoft Azure
• Microsoft Fabric
• Power BI
• Azure DevOps
• Strong understanding of cloud data warehouse design
• Microsoft Azure
• Microsoft Fabric
• Power BI
• Azure DevOps
• Strong understanding of cloud data warehouse design
Databases & Storage
• PostgreSQL (explicit requirement for Cortex)
• Supabase (PostgreSQL-based)
• PostgreSQL (explicit requirement for Cortex)
• Supabase (PostgreSQL-based)
Vector & AI-Ready Data Stores (Mandatory)
• Pinecone, Weaviate, PostgreSQL + pgvector
• Schema design for embeddings, vector search, RAG, and semantic workloads
• Pinecone, Weaviate, PostgreSQL + pgvector
• Schema design for embeddings, vector search, RAG, and semantic workloads
Governance, Security & Observability
• RBAC, environment isolation, compliance-ready architectures (SOC 2, ISO 27001, GDPR principles)
• Monitoring standards for pipelines, data quality, failures, and anomalies
• RBAC, environment isolation, compliance-ready architectures (SOC 2, ISO 27001, GDPR principles)
• Monitoring standards for pipelines, data quality, failures, and anomalies
🤝 Collaboration & Leadership
• Act as the data lead within Engineering, not an IT-only DBA role.
• Provide architectural guidance to DBAs, data engineers, and BI teams.
• Bridge Engineering, IT, DevOps, Security, and Analytics.
• Drive documentation of data models, pipelines, migrations, lineage, and standards.
• Provide architectural guidance to DBAs, data engineers, and BI teams.
• Bridge Engineering, IT, DevOps, Security, and Analytics.
• Drive documentation of data models, pipelines, migrations, lineage, and standards.
âś… Qualifications
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
• 7+ years of experience in data architecture, data engineering, or platform roles.
• Expert knowledge of SQL Server, PostgreSQL, data modeling, and hybrid architectures.
• English fluency (C1+) required.
• 7+ years of experience in data architecture, data engineering, or platform roles.
• Expert knowledge of SQL Server, PostgreSQL, data modeling, and hybrid architectures.
• English fluency (C1+) required.
Preferred Certifications
• Microsoft Azure Data Engineer Associate
• Microsoft Azure Database Administrator Associate
• Microsoft Azure Data Engineer Associate
• Microsoft Azure Database Administrator Associate
🚀 Join a global team where data architecture powers AI, analytics, and the future of logistics.
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