DataOps Engineer Lead for Databricks & CI/CD

Nodi; Barcelona; Híbrido; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

dLocal is seeking a DataOps Technical Referent to help build a reliable, secure, and scalable data-mesh platform. You’ll combine hands-on engineering with technical leadership across cloud, data engineering, and analytics, focusing on Databricks and IaC.

You will work in a fast-moving environment, collaborating with cross-functional teams to automate data operations, improve platform reliability, and drive data governance.

Formación

• Proven experience building data platforms and Databricks administration.
• Strong Python, Bash, and SQL skills with IaC experience.
• Experience with cloud providers AWS, and knowledge of GCP helpful.

Responsabilidades

• Build and maintain Python components, Terraform modules, and CI/CD pipelines.
• Administer Databricks workspaces and platform capabilities.
• Manage Databricks infrastructure as code across environments.
• Support IAM, permissions, secrets, networking, and integrations.
• Monitor Databricks workloads for reliability, performance, and cost.
• Integrate APIs and platform tools to automate data operations.
• Deploy and oversee cloud infrastructure for reliability and performance.
• Develop data models, platform best practices, and technical documentation.
• Establish DataOps and DevOps practices, processes, and governance.
• Collaborate with stakeholders to understand needs and drive resolution.

Conocimientos

Python

Terraform

Databricks

AWS

Kubernetes

CI/CD

Databases

GitHub

Docker

Security

Herramientas

Git

Docker

Kubernetes

Helm

Terraform

Databricks

Descripción del empleo

dLocal is seeking a DataOps Technical Referent to help build a reliable, secure, and scalable data-mesh platform. You’ll combine hands-on engineering with technical leadership across cloud, data engineering, and analytics, focusing on Databricks and IaC.

You will work in a fast-moving environment, collaborating with cross-functional teams to automate data operations, improve platform reliability, and drive data governance.