Senior Databricks Platform Engineer (Azure)

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SeniorHybryda·WarszawaFull-time·Umowa o pracę

#463171·Dodano 3 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

Python SQL Azure Databricks Terraform REST API CI/CD GitHub

Podsumowanie oferty

Operate and evolve a data and AI platform built on Azure Databricks, evaluating and governing new platform capabilities for secure, scalable adoption. Build automation, self-service tools, and reusable agent instructions to support platform users and AI-assisted software development.

Wymagania

4+ years of hands-on Azure Databricks experience, including workspace administration, compute configuration, permissions, and cost management.
Proficiency in Python and SQL sufficient to analyze platform logs.
Practical experience with REST APIs, Terraform, and Azure networking, including Private Endpoints and vNETs, and Microsoft Entra ID.
Experience with CI/CD using Azure DevOps, GitHub Actions, or similar tools.
Strong problem-solving, documentation, and cross-functional communication skills.

Preferred Qualifications:

Deep understanding of the Databricks control plane, compute planes, model serving architecture, and Genie.
Experience governing Databricks at enterprise scale.
Experience building scalable self-service platforms for Engineers (platform engineering).
Hands-on experience with AI coding agents and creating reusable context layers that encode engineering standards.
Familiarity with policy-as-code, automated compliance checks, and configuration drift detection.
Experience with Azure Monitor, Log Analytics, Databricks audit logs, and system tables.
Understanding of security risks, including sensitive-data exposure, prompt injection, and excessive tool permissions.
Relevant, current Databricks or Microsoft Azure certifications.

Obowiązki

Feature Evaluation:

Track the Databricks roadmap, evaluate new features through proofs of concept, and assess security risks, cost implications, and governed scalability readiness.
Document recommendations and adoption requirements, and work with Engineers, Architects, and Product Owners to deploy capabilities at scale.

Adoption and AI-Assisted Engineering Enablement:

Develop reusable configurations, implementation patterns, and documentation.
Build, test, and maintain agent skills and instructions that help coding agents apply Databricks security, governance, testing, and performance best practices throughout the SDLC.

CI/CD and Automation:

Build pipelines for Databricks account configuration changes and safely perform these changes.
Automate administration and validation using version control, peer review, and controlled deployment practices.

Governed Self-Service Enablement:

Build self-service tools for teams to request and enable approved Databricks capabilities within predefined governance guardrails, such as through PRs to Terraform repositories or APIs.

Security Evaluation:

Partner with Information Security to review capabilities before production adoption at scale.
Implement access controls and technical guardrails.
Promote reusable patterns and periodically review existing implementations to address exceptions, retire obsolete approaches, and reduce technical debt.

Data-Driven Governance:

Use SQL to analyze Databricks system tables.
Build dashboards and define metrics to track feature adoption, usage patterns, and costs.
Use insights to prioritize platform changes and measure their impact.

Platform Operations:

Manage Databricks account configuration, monitoring, reliability, and costs.
Troubleshoot complex platform issues and maintain operational runbooks.
Advise platform users on best practices.

Benefity

Corporate and functional training.
Industry certifications, including ITIL, DevOps, and the Microsoft portfolio.
Private health care.
Sport cards and access to an in-office fitness center.
P&G stock options and saving plans.
Lunch subsidy.
Regular salary increases and possible promotions.
Mentoring programs and training.

Szkolenia wewnętrzne

Opieka zdrowotna

Karta sportowa

Udziały pracownicze

Procter & Gamble

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