Data Architect

Build the Future with AspenView Technology Partners

At AspenView, we are passionate about transforming the way organizations approach technology. We specialize in creating high-performing, nearshore IT teams to help North American clients innovate faster and more efficiently.

As we continue to grow, we’re looking for exceptional people to join our team and help drive impactful change across industries.

Why Join AspenView?

At AspenView, we’re more than a nearshore IT partner, we’re a people-first, purpose-driven company that believes great culture drives great outcomes. We’re passionate about connecting talent and technology to deliver measurable value for clients, and meaningful career paths for our people.

About the Role

AspenView is seeking a Senior Data Architect with a strong data engineering foundation to join a large-scale data modernization initiative for a financial services client. In this role, you will own the physical design and engineering of the analytical data platform, building dimensional models on Amazon Redshift and the transformation and orchestration layers that power enterprise reporting and Business Intelligence.

You will work within a Data Mesh operating model alongside business-focused data modelers, domain teams, and BI stakeholders, turning logical designs into performant, well-governed data products. This is a full-time position, contractor agreement, with 100% dedication to the project, based in Buenos Aires, Argentina.

What You Will Do

• Physical Dimensional Modeling: Design, implement, and evolve physical dimensional models (facts, dimensions, and aggregates) in Amazon Redshift, translating conceptual and logical designs into scalable, production-ready structures.
• Redshift Performance & Optimization: Define distribution styles, sort keys, compression, and workload management strategies, and continuously tune queries and storage to meet performance and cost targets.
• Transformation Engineering with dbt: Build and maintain modular, tested, and well-documented dbt models, establishing standards for layering, naming, testing, and version control across the transformation codebase.
• Pipeline Orchestration with Airflow: Design and operate Airflow DAGs that orchestrate ingestion and transformation workflows, including dependency management, scheduling, retries, monitoring, and alerting.
• Data Mesh Enablement: Help domain teams deliver discoverable, reliable, and interoperable data products, applying shared modeling conventions, data contracts, quality checks, and governance standards.
• BI Enablement & Collaboration: Write and review advanced SQL, support BI and analytics teams with performant semantic structures, and partner with architects and business modelers to align technical delivery with business requirements.