DataOps Engineer — Databricks & Cloud Infra Automation

Dlocal LLP; Tandil; On-site; ARS 108,178,000 - 169,994,000; Full time

Job summary

dLocal LLP is seeking a DataOps Technical Referent to build and operate a reliable, secure, and scalable data-mesh platform. You will blend hands-on engineering with leadership, automating infrastructure and workflows, and turning requirements into practical solutions across cloud, data engineering, and analytics.

You’ll focus on Databricks administration and infrastructure as code, working in a fast-moving environment with ambiguity, collaborating across teams and driving platform improvements

Qualifications

• Strong Python skills and SQL knowledge.
• Experience with Terraform, Git workflows, and CI/CD.
• Databricks administration and cloud experience (AWS preferred).

Responsibilities

• Build and maintain Python components, Terraform modules, and CI/CD pipelines to automate data platform processes and infrastructure.
• Administer and support Databricks workspaces and platform capabilities, including workspace configuration, access controls, compute policies, and operational standards.
• Manage Databricks infrastructure as code, applying reusable, version-controlled patterns for provisioning and configuration across environments.
• Support Databricks identity and access management, permissions, secrets, networking, and integrations in partnership with cloud and security teams.
• Help operate and optimize Databricks workloads, monitoring reliability, performance, and cost; investigate issues and coordinate their resolution.
• Implement and monitor data pipelines and platform integrations to ensure reliability and governance.

Skills

Python

SQL

Terraform

CI/CD

Databricks

AWS

Docker

Kubernetes

Data modeling

Tools

Docker

Kubernetes

Helm

GitHub

Terraform

Job description

dLocal LLP is seeking a DataOps Technical Referent to build and operate a reliable, secure, and scalable data-mesh platform. You will blend hands-on engineering with leadership, automating infrastructure and workflows, and turning requirements into practical solutions across cloud, data engineering, and analytics.

You’ll focus on Databricks administration and infrastructure as code, working in a fast-moving environment with ambiguity, collaborating across teams and driving platform improvements