Senior Data Platform Engineer

Avenga; Municipio de Rincón de los Sauces; Hybrid; ARS 1,800,000 - 3,200,000; Full time

Job summary

Avenga is seeking a Senior Data Platform Engineer in CABA to industrialize Databricks as a corporate data platform. The role focuses on standardizing, automating, observable, and reliable data products while reducing manual tasks and dependencies.

You will build reusable patterns and self-service capabilities to enable scalable data work. You will design and implement CI/CD pipelines, develop IaC with Terraform, and automate provisioning of Databricks workspaces, permissions, and policies.

Qualifications

• 5+ years in Data Platform Engineering, DataOps, DevOps, SRE, or similar roles.
• Hands-on Databricks in enterprise environments.
• Experience with CI/CD pipelines and Git-based workflows.
• Bachelor's degree in Engineering/IT/CS/IS; English intermediate or higher.

Responsibilities

• Design and implement CI/CD pipelines for Databricks across environments.
• Develop and maintain Terraform IaC solutions.
• Automate provisioning and management of Databricks resources and policies.
• Create templates and standards for onboarding data pipelines.
• Automate onboarding of users and services on the data platform.
• Implement observability with monitoring, logging, alerts, and metrics.
• Define operational reliability practices including SLAs and SLOs.
• Improve platform reliability, scalability, and capacity.
• Support FinOps through cost allocation and tagging.

Skills

Data Platform Engineering

DataOps

DevOps

SRE

Databricks

CI/CD pipelines

Git workflows

Infrastructure as Code

Cloud platforms

IAM

English (intermediate)

Education

Bachelor's degree in Engineering/IT/CS/IS

Tools

Terraform

Databricks

Git

CI/CD tooling

Cloud platforms

Job description

We are looking for a Senior Data Platform Engineer in CABA to join our team and industrialize Databricks as corporate data platform, ensuring a standardized, automated, observable, and reliable model for developing and operating data products. The mission is to reduce manual tasks and individual dependencies by enabling reusable patterns and self-service capabilities, allowing the platform to scale without a proportional increase in the team’s operational burden.

Core skills you’ll bring

• 5+ years of experience in Data Platform Engineering, DataOps, DevOps, Site Reliability Engineering (SRE), or similar roles.
• Hands‑on experience with Databricks in enterprise‑scale environments.
• Strong experience implementing and managing CI/CD pipelines and Git‑based development workflows.
• Proven experience with Infrastructure as Code, including Terraform (required) or equivalent technologies.
• Experience with cloud platforms, identity and access management (IAM), networking, secrets management, service principals, and infrastructure automation.
• Bachelor's degree in Engineering, Information Technology, Computer Science, Information Systems, or a related field.
• English - intermediate or higher
• Ability to visit the office once a week

The impact you’ll create

• Design and implement CI/CD pipelines for Databricks, enabling controlled promotion of artifacts across environments.
• Develop and maintain Infrastructure as Code (IaC) solutions using Terraform and other automation tools.
• Automate provisioning and management of Databricks workspaces, permissions, compute resources, service principals, and platform policies.
• Create reusable templates, frameworks, and engineering standards for onboarding new products and data pipelines.
• Automate onboarding processes for users, applications, and services across the data platform.
• Implement and maintain observability capabilities, including monitoring, logging, alerting, and operational metrics.
• Define and manage operational reliability practices, including SLAs, SLOs, retry mechanisms, reprocessing workflows, and recovery procedures.
• Improve platform reliability, scalability, performance, and capacity management.
• Support FinOps initiatives through cost allocation, tagging strategies, usage tracking, and optimization activities.
• Document platform standards, architecture decisions, operational procedures, and runbooks.
• Drive a self‑service culture by developing platform capabilities that reduce manual intervention and increase engineering productivity.