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    Job · 11375399

    REMOTEFULLTIME

    Sr. Staff Platform/Data Reliability Engineer, Databricks

    Shield logo

    Shield

    Remote · remote · Posted 69d ago

    Sourced fromNaukri
    Undisclosed12–17 yrsfulltimeRemote

    About a minute. You'll make an account on the way through.

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    Section · 01

    About this role

    The Sr. Staff Platform / Data Reliability Engineer is responsible for making Databricks a reliable, secure, scalable, and operationally mature platform for enterprise use. This role focuses on the platform itself rather than domain-specific business modeling, ensuring the lakehouse can support multiple domains, regulated data handling, and a growing set of production workloads without becoming fragile, expensive, or hard to govern.

    This role partners closely with the Senior Staff Data Engineer, who focuses more heavily on ingestion and medallion implementation patterns, and with the existing Cloud & Infrastructure team, which owns cloud accounts, networking, and foundational infrastructure. The Platform / Data Reliability Engineer owns the Databricks operational layer that sits above that foundation: reliability, observability, deployment standards, compute and job policies, and platform enablement patterns for internal users.

    What you'll do

    • Own operational excellence for the Databricks platform, including monitoring, alerting, observability, incident response support, and production runbook patterns for data jobs and platform services.
    • Define and maintain CI/CD and promotion standards for Databricks assets, including workflows, jobs, notebooks, code packages, infrastructure configuration, and environment promotion from dev to prod.
    • Design and maintain platform standards for job orchestration, cluster and compute policies, service principal usage, environment isolation, and production execution reliability.
    • Establish reusable operational templates and enablement patterns for new domains onboarding to Databricks, including logging conventions, job tagging, metadata capture, and support handoff expectations.
    • Partner with the Senior Data Engineer to ensure ingestion and medallion patterns are implemented in a way that is observable, recoverable, cost-aware, and secure in production.
    • Work with the cloud/infrastructure team to align Databricks configuration and usage patterns with broader enterprise cloud standards, especially where commercial and future government-hosted environments are involved.
    • Help enforce technical controls for data segregation, access boundaries, and operational compliance in a highly regulated environment.
    • Track and improve platform health metrics such as job success rates, incident trends, data pipeline reliability, cost efficiency, and environment drift.
    • Document platform standards, operational expectations, and support models so the Databricks platform can scale beyond a small founding team.
    • Mentor internal engineers who are growing into platform responsibilities, helping expand Databricks operational knowledge within the team.

    Required qualifications

    • 12+ years of relevant experience in data platform engineering, platform operations, site reliability engineering, or modern cloud data infrastructure.
    • Hands-on experience with Databricks or a closely related cloud data platform in production environments.
    • Experience designing or operating CI/CD, environment promotion, version control, and deployment automation for data platforms and pipelines.
    • Strong understanding of platform operations concepts such as observability, monitoring, alerting, incident management, and reliability engineering.
    • Experience with compute policy design, workload isolation, service principals, and secure production execution patterns on cloud data platforms.
    • Ability to work effectively in a regulated or security-sensitive environment with strong expectations around access control, auditability, and operational discipline.
    • Strong collaboration skills and comfort partnering with cloud/infrastructure, security, data engineering, and analytics stakeholders.

    Preferred qualifications

    • Databricks certification and/or strong demonstrated expertise with Delta Lake, Unity Catalog, Workflows, and Databricks Asset Bundles.
    • Experience with infrastructure-as-code and platform automation in enterprise environments.
    • Experience supporting commercial and government or otherwise segregated environments with different compliance and access requirements.
    • Experience in defense, aerospace, federal, or another regulated industry.


    Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

    Sourced from naukri

    Section · 02

    Skills

    AutomationIncident ManagementSimulationAerospaceMonitoringmetadataAnalyticsComputer NetworksGITRecruitment

    Section · Company

    About Shield

    Shield logo

    Shield

    IT Services & Consulting

    25

    employees

    2008

    18 years old

    San Francisco, California

    United States

    ₹16.2L PA avg

    Avg at Shield

    About

    Shield provides a fraud intelligence platform for digital businesses, focusing on the identification and prevention of fraudulent activities through advanced device recognition.

    Industries

    Artificial Intelligence (AI)Cyber SecurityFraud DetectionInformation TechnologyMachine LearningPayments

    Employee ratings

    10 reviews

    4.4/ 5

    Culture

    3.7

    Career growth

    2.7

    Work-life

    3.9

    Employees rate it well for

    Work-Life Balance45Overall Company44

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