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    Job · 19538666

    BENGALURU · FULLTIME

    Senior Data Platfrom Engineer

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    e-Hireo

    Bengaluru · onsite · Posted 23d ago

    Sourced fromFoundit
    Not disclosed3–8 yrsfulltimeBengaluru

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    Section · 01

    About this role

    JOB DESCRIPTION

    Experience : 3 - 8 Yrs

    Location : Bengaluru

    Designation : Senior Data Platfrom Engineer

    Job description

    • Architect and drive large-scale distributed systems, data platforms, and backend services that are highly available, cost-efficient, secure, and extensible
    • Establish platform vision and evolve foundational frameworks with multi-tenant, self-serve, and platform-first thinking
    • Design for scale and resilience — enforcing clean architecture, observability, fault tolerance, extensibility, and performance
    • Lead end-to-end initiatives from problem definition to production rollout, balancing business impact with long-term technical sustainability
    • Mentor and grow engineers (including Senior Engineers), setting technical direction and raising the quality bar
    • Make deep technical trade-offs explicit — connecting system internals, architectural decisions, and platform costs
    • Champion best practices in code quality, instrumentation, design patterns, and cloud-native development
    • Influence cross-team architecture by partnering with product, infra, and data science
    • Drive innovation by identifying gaps, proposing bold solutions, and creating reusable building blocks
    • Demonstrate thought leadership by anticipating scale challenges and ensuring security/compliance

    Must Haves

    • Deep expertise in modern data lake/warehouse and distributed data architectures — hands-on with Trino, Presto, Iceberg/Delta Lake, Spark, Kafka, and large-scale storage/compute separation
    • Coding proficiency in Golang or Python
    • Proven track record building and scaling multi-tenant data platforms, with awareness of cost efficiency, security, compliance, and operational excellence
    • Architectural intuition at scale — evaluating trade-offs between performance, latency, fault-tolerance, extensibility, and cost
    • Strong system internals knowledge (compilers, query engines, storage formats, distributed consensus, networking, JVM internals, or equivalent)
    • Hands-on leadership — mentoring senior engineers and driving adoption of engineering best practices

    Sourced from foundit

    Section · 02

    Skills

    Design Patternscode quality instrumentationlarge-scale storage compute separationsystem internals knowledgeApache SparkApache KafkaDeltaicebergCompilersComputer NetworksPrestoTrinoCloud-Native DevelopmentGolangJVM internalsPythonquery enginesStorage Formatsdistributed consensusdistributed data architectures

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