Proven experience as a Data Architect, Data Lead, or senior Data Engineer with architecture ownership responsibilities.Deep hands-on experience designing and governing production data pipelines built with dbt and Apache Airflow.Strong experience with Amazon Redshift data warehouse architecture and data mart design.Strong SQL and data modeling skills, with the ability to define and enforce modeling standards across a team, including data lineage, traceability, and auditability standards for a pipeline.Strong hands-on experience with Python for pipeline and tooling development.Experience with MySQL or similar relational databases, and familiarity with AWS cloud-native services such as S3, Lambda, EC2, and RDS.Comfort working within a regulated or compliance-driven environment (e.g., SOC-2, HIPAA, or similar), including justifying technical decisions for audit purposes.Experience providing technical leadership and mentorship to other data engineers.Experience working in a sprint-based agile delivery model, coordinating with cross-functional engineering teams.Strong documentation and communication skills; able to work effectively with both technical and non-technical stakeholders, including project-side architecture and product leadership.Advanced English.Comfortable using and evaluating AI-assisted development tools — AI coding assistants, code generation, or automated review tools — to improve team delivery speed and quality.We are looking for someone able toOwn technical architecture and design standards for the data pipelines supporting assigned projects, reviewing and approving technical designs for new pipeline components, Airflow DAGs, and data mart changes.Define and evolve dbt model standards — naming conventions, layering, and testing practices — ensuring consistency, quality,



and maintainability across the data team's model layer.Provide technical leadership and direction to the data engineering team: architectural guidance, design/code review, and mentoring for data engineers and analytics engineers on best practices.Partner with project stakeholders and the delivery team to align technical implementation with the project's architecture, roadmap, and sprint cadence, representing the data team in architecture discussions and technical planning.Own the technical strategy for addressing technical debt — investigating root causes of significant issues and proposing architecture-level remediation plans — and evolving pipeline architecture to support future features.Ensure the pipeline architecture supports end-to-end traceability, auditability, and compliance with SOC-2 controls and applicable regulated data handling requirements (e.g., HIPAA), documenting architecture decisions, standards, and data lineage.Support knowledge transfer and onboarding as project team composition changes, guiding the team's approach so documentation and standards remain transferable.Track architecture and technical debt work using the project's tooling (e.g., JIRA), and ensure code changes follow branching and CI/CD standards (e.g., GitLab).
Support incident response and root-cause analysis for architecture-level or systemic pipeline issues.Other valuable skillsExperience with drug supply chain, pharmacy licensing, or similar healthcare regulatory frameworks.Experience with state-level or federal regulatory and compliance systems.Prior work with not-for-profit or governmental organizations.Experience with GitLab CI/CD, AWS CloudWatch, AWS Secrets Manager, or infrastructure-as-code practices.Familiarity with C#.
Experience presenting architecture decisions to technical or product leadership.
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📌 Data Architect (Buenos Aires)
🏢 Light-It
📍 Buenos Aires