Staff DataOps Engineer

About the role

dLocal is a fintech company providing payment infrastructure for global merchants in emerging markets. It is looking for a Staff DataOps Engineer (referred to as a DataOps Technical Referent) to help build and run a reliable, secure and scalable data-mesh platform. The role combines hands-on engineering with technical leadership, working across cloud infrastructure, data engineering and analytics, with a focus on Databricks and infrastructure as code.

Key responsibilities

• Build and maintain Python components, Terraform modules and CI/CD pipelines to automate data platform processes and infrastructure.
• Administer and support Databricks workspaces, including workspace configuration, access controls, compute policies and operational standards.
• Manage Databricks infrastructure as code with reusable, version-controlled patterns across environments.
• Support Databricks identity and access management, permissions, secrets, networking and integrations with cloud and security teams.
• Help operate and optimise Databricks workloads, monitoring reliability, performance and cost, and investigating issues.
• Integrate APIs and platform tools to automate data operations and connect infrastructure and services.
• Deploy, maintain and oversee cloud infrastructure, and help develop data models, best practices and technical documentation.
• Establish and improve DataOps and DevOps practices, policies and processes.
• Work with stakeholders to understand needs, clarify requirements and drive issues to resolution, and contribute to platform architecture and governance decisions.

Required profile

• Thrives in fast-moving environments, is comfortable with ambiguity and enjoys learning and collaborating across teams.
• Strong troubleshooting and process-improvement skills, with attention to operational reliability, security and detail.
• Ability to collaborate across teams, communicate technical options clearly and own work with limited guidance.
• Adaptability and initiative, comfortable with rapid iteration and finding creative solutions.
• AWS associate- or professional-level certification is a plus; experience with streaming data (Kafka or AWS Kinesis) and event-driven architectures is also valued.

Required skills

• Strong Python; familiarity with Bash and SQL.
• Terraform, Git-based workflows and CI/CD.
• Databricks administration and platform automation.
• Cloud environments, especially AWS (GCP experience also valuable).
• Databases, data warehouses, data lakes, data pipelines and data modelling.
• GitHub, Docker, Kubernetes and Helm.