DataOps Tech Lead: Hybrid, Databricks & Automation

Nodi; Buenos Aires; Hybrid; ARS 139,474,000 - 201,463,000; Full time

Job summary

dLocal is seeking a DataOps Technical Referent to build and operate a reliable, secure, and scalable data-mesh platform. You will combine hands-on engineering with technical leadership, automating infrastructure and workflows, and helping teams translate requirements into practical solutions.

You’ll work across cloud infrastructure, data engineering, and analytics, focusing on Databricks administration and infrastructure as code, in a fast-moving environment with ambiguity.

Qualifications

• Strong Python skills; familiarity with Bash and the ability to work confidently with SQL.
• Practical experience with Terraform and infrastructure as code, Git-based workflows, and CI/CD.
• Experience administering or operating Databricks, ideally including workspace configuration, access management, compute, and platform automation.
• Familiarity with cloud environments and services, particularly AWS; experience with GCP is also valuable.
• Understanding of databases, data warehouses, data lakes, data pipelines, and data modeling.
• Familiarity with development and data tools such as GitHub, Docker, Kubernetes, and Helm.
• 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: you're comfortable with rapid iteration, ambiguity, and finding creative solutions.
• AWS associate- or professional-level certifications are a plus.
• Experience with streaming data concepts and technologies, such as Kafka or AWS Kinesis, including building or supporting reliable streaming pipelines.
• Understanding of event-driven architectures, message delivery and processing patterns, and monitoring/troubleshooting of streaming workloads.

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.
• Integrate APIs and platform tools to automate data operations, trigger and monitor processes, and connect infrastructure and services.
• Deploy, maintain, and oversee cloud infrastructure to meet reliability and performance needs.
• Help develop data models, platform best practices, and technical documentation for users.
• Establish and improve DataOps and DevOps practices, policies, and processes.
• Work with stakeholders to understand needs, clarify requirements, and propose solutions; take ownership of issues and drive them through to resolution.
• Contribute to platform architecture and technology decisions, weighing trade-offs and promoting sound data access, stewardship, and governance practices.

Skills

Python

Bash

SQL

Terraform

CI/CD

Databricks

AWS

GCP

Docker

Kubernetes

Helm

GitHub

Data modeling

Data pipelines

Kafka

Kinesis

Event-driven

Tools

Databricks

Terraform

GitHub

Docker

Kubernetes

Helm

Job description

dLocal is seeking a DataOps Technical Referent to build and operate a reliable, secure, and scalable data-mesh platform. You will combine hands-on engineering with technical leadership, automating infrastructure and workflows, and helping teams translate requirements into practical solutions.

You’ll work across cloud infrastructure, data engineering, and analytics, focusing on Databricks administration and infrastructure as code, in a fast-moving environment with ambiguity.