Data Architect

Light-it; Buenos Aires; Presencial; ARS 2.000.000 - 2.800.000; Jornada completa

Descripción de la vacante

Light-it is seeking a senior Data Architect to own data pipeline architecture, standards, and governance. You will lead design reviews for Airflow DAGs and dbt models while shaping data mart design within a regulated environment.

You will mentor data engineers, collaborate with stakeholders, and steer debt remediation and architectural planning to align with project roadmaps and compliance needs.

Formación

• Proven experience as a Data Architect, Data Lead, or senior Data Engineer with architecture ownership responsibilities.
• 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.

Responsabilidades

• Own 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.

Conocimientos

Data architecture

dbt

Apache Airflow

Redshift

SQL

Data modeling

Python

MySQL

AWS services

Leadership

Agile

Documentation

English

AI tools

Healthcare/regulatory

Herramientas

dbt

Apache Airflow

Redshift

Python

MySQL

AWS (S3, Lambda, EC2, RDS)

GitLab CI/CD

JIRA

AWS CloudWatch

AWS Secrets Manager

Descripción del empleo

• 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 to

• Own 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 skills

• Experience 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.