Senior DevOps / DataOps Engineer – Databricks Platform

Job not on LinkedIn

🔥 16 hours ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 24%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Compass

WebsiteLinkedInAll Job Openings

10,000+ employees

🏠 Real Estate

📱 Media

Real Estate • Media

Compass is a real-estate-focused content and services site that provides detailed market analysis, buying/selling/renting guides, mortgage and financing information, and home improvement and renovation advice. The site offers resources for homebuyers, sellers, renters, agents, and real estate investors — including articles on appraisals, affordable housing, investment strategies, staging and property maintenance. Compass aims to help users make informed decisions across the housing lifecycle through timely market updates and practical how-to content.

📋 Description

• Design, implement, and evolve the Databricks platform’s CI/CD pipeline, automatically promoting artifacts across development, staging, and production. • Standardize the packaging and deployment of workloads with Databricks Asset Bundles, creating reusable templates for data domains and squads. • Implement and maintain IaC with Terraform and the Databricks provider for workspaces, compute policies, service principals, secret scopes, and Unity Catalog objects. • Define and evolve versioning, branching, code review, and release management strategies using Bitbucket, GitHub, or GitLab. • Build and maintain pipelines as code, including deployment, versioning, rollback, and promotion across environments. • Establish automated quality gates with unit and integration tests, data contract validation, static analysis, linting, and minimum coverage metrics. • Automate governance and security controls, including permissions through Unity Catalog, RBAC, cluster and cost policies, environment segregation, secrets management, and auditing. • Promote software engineering best practices across platform, migration, and analytics engineering squads. • Contribute to architecture decisions, technical standards, documentation, and technical mentoring. • Support monitoring and troubleshooting of pipelines, workloads, and infrastructure using Datadog or similar tools.

🎯 Requirements

• Experience in DevOps, DataOps, or related fields, with a track record of building and enhancing end-to-end CI/CD pipelines. • Experience with CI/CD as code using Bitbucket Pipelines, GitHub Actions, or GitLab CI. • Strong knowledge of Git, including Trunk-Based Development, GitFlow, or similar approaches; pull requests, code review, branch protection, and release versioning. • Experience with Databricks Asset Bundles, Databricks CLI, and the packaging and deployment of jobs, workflows, and configurations. • Advanced Python skills, including project structuring and modularization, library development, wheel packaging, and artifact publishing. • Experience with automated testing, including unit and integration testing with Pytest or similar tools, mocks, fixtures, and coverage metrics. • Experience with Terraform, particularly automating and managing resources using the Databricks provider. • Experience working in cloud environments, preferably AWS or Azure, with knowledge of identity, storage, networking, and managed services. • Solid SQL knowledge for data pipeline validation, analysis, and troubleshooting. • Nice to have: experience migrating legacy Data Warehouses to Lakehouse architectures. • Nice to have: knowledge of Databricks platform administration and support, including workspaces, clusters, jobs, workflows, and compute policies. • Nice to have: experience with Unity Catalog, data governance, RBAC, secrets management, environment segregation, and automated audit controls. • Nice to have: experience with observability and monitoring using Datadog or equivalent tools. • Nice to have: experience with data platforms, Data Engineering, Data Warehousing, and the modernization of enterprise environments.