1178 - Sr. Data Architect

Role overview Own the architecture of a Databricks lakehouse and guide its implementation across data pipelines, governance, infrastructure, and engineering practices. You will lead major platform work, including migrations, while helping teams make sound technical decisions and exploring practical AI use cases on the data platform.

Responsibilities - Design and own an end-to-end lakehouse architecture on Databricks using bronze, silver, and gold data layers. - Build and tune batch and streaming pipelines with PySpark, Spark SQL, and Python. - Lead migrations from legacy warehouses or Hadoop-based platforms, targeting measurable improvements in cost and runtime. - Establish governance practices for access control, auditing, lineage, and regulatory compliance. - Define data models for analytical and operational use, and set standards for testing, CI/CD, code review, reusable packages, and asset deployment. - Manage infrastructure with Terraform, guide cloud cost controls, prototype AI platform use cases, and mentor engineers.

Requirements - 10 or more years in data engineering, including at least 5 years using Databricks and Spark in production. - Strong Python and PySpark skills, advanced SQL, and working knowledge of Scala. - Experience designing data lakes, warehouses, and lakehouses, including leading a substantial migration. - Production experience with at least one major cloud provider: AWS, Azure, or GCP. - Hands-on data governance experience with Unity Catalog, access controls, lineage, and auditing. - Solid software engineering practice with Git, automated testing, and CI/CD, plus infrastructure-as-code experience with Terraform. - Ability to explain architectural trade-offs to technical and non-technical audiences and mentor other engineers. - English proficiency at C1 level or higher.

Nice to have - Databricks or cloud architecture certifications and experience across multiple cloud providers. - Experience building agentic or retrieval-augmented AI systems using tools such as LangChain, LangGraph, MLflow, model APIs, and vector databases. - High-volume real-time or IoT data processing, or experience in finance, telecom, payments, or SaaS data. - Spanish or Portuguese language skills.

Benefits and work setup - Full-time contract through a payroll platform. - Remote work, based in Latin America and assigned to a client.