Senior Data Architect

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Develop and enhance strategies for enterprise data architecture, encompassing data models, data lakes, and data warehouses.

• Lead the design and execution of ETL/ELT pipelines to facilitate analytics, reporting, and AI/ML workloads.

• Architect and implement frameworks for Master Data Management (MDM) to ensure data quality, consistency, and governance across systems.

• Design and construct modern data platforms utilizing Databricks and Microsoft Fabric.

• Architect cloud-native data solutions on AWS, ensuring scalability, security, and cost-effectiveness.

• Establish data governance standards, metadata management practices, and frameworks for data lineage.

• Collaborate with data science and AI teams to create data architectures that support machine learning, GenAI, and agentic system applications.

• Partner with both business and technical stakeholders to translate data requirements into scalable architectural solutions.

• Evaluate and recommend tools, technologies, and best practices for data integration, storage, and processing.

• Provide technical leadership and mentorship to data engineering teams.

• Troubleshoot complex issues related to data pipelines and platforms, driving root cause analysis and long-term solutions.

• Foster continual improvement in data architecture, performance, and observability.

⛳️ Requirements

• Over 8 years of experience in data architecture, data engineering, or related fields.

• Extensive hands-on experience in designing data models (conceptual, logical, physical) for enterprise systems.

• Demonstrated experience in building and optimizing ETL/ELT pipelines.

• Practical experience in implementing Master Data Management (MDM) solutions.

• Strong expertise with Databricks for data engineering and analytics tasks.

• Familiarity with Microsoft Fabric for integrated data and analytics solutions.

• Significant experience with AWS data services (e.g., S3, Glue, Redshift, RDS, Lake Formation).

• Understanding of AI/ML data requirements, including feature engineering and data preparation for GenAI and LLM-based systems.

• Strong knowledge of data governance, data quality, and metadata management practices.

• Proficiency in SQL and familiarity with Python or other data engineering languages.

• Excellent analytical and problem-solving abilities, with the capacity to convey technical concepts to non-technical stakeholders.

🏝️ Benefits

• Health insurance

• Paid time off

• Flexible work options

• Professional development opportunities