Description: Behavioral Skills; Technical Leadership * High ability in self-management. * Definition of technical standards and best practices for the team. Business Vision * Understanding stakeholders' needs and translating them into scalable solutions. * Ability to prioritize deliveries based on business value. Communication * Clarity in explaining complex concepts to non-technical audiences. * Skill in documentation and storytelling with data. Resilience and Ownership * Responsibility for the complete data lifecycle (from ingestion to consumption). * Ability to solve problems under pressure. Collaboration and Teamwork * Effective work in multidisciplinary squads (analysts, data scientists, engineers). * Experience with DevOps culture and agile methodologies (Scrum or Kanban). Technical Knowledge Snowflake and Data Modeling * Dimensional modeling (fact/dimension). * Performance optimization (clustering keys, warehouse sizing). * Automated ingestion with Snowpipe. * Creation of ELT pipelines within Snowflake (Tasks, Streams, Procedures in Python/SQL). * Integration with AWS (S3 - Snowflake). Orchestration and Pipelines * Experience with Airflow (preferred). * Knowledge in CI/CD (GitHub Actions, GitLab CI or Bitbucket). Infrastructure and DevOps * IaC (Infrastructure as Code): Terraform or CloudFormation. * Containers: Docker (Kubernetes is a plus). * Application of data security and governance best practices. DataOps / Observability * Pipeline monitoring. * Data Quality (Great Expectations or dbt tests). * Structured logging. Opportunity Context * Focus on data engineering and requirement gathering. * Participation in the initial Discovery phase of projects. * Ability to understand and document requirements, then develop artifacts. * Knowledge in Databricks. * Desirable knowledge in AWS architecture. 251119020246262704