Data QA Engineer

5 - 8 years

5 - 9 Lacs

Posted:5 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

We are seeking a highly skilled and detail-oriented

Software Test Engineer (Data QA)

with hands-on experience in validating

real-time data streaming platforms

,

cloud-native architectures

, and

modern data ecosystems

. The ideal candidate will be proficient in testing complex data pipelines, ensuring data integrity, and validating system reliability within distributed environments.

Key Responsibilities:

  • Design, implement, and execute

    manual and automated test strategies

    for

    real-time streaming use cases

    using

    Azure Service Bus

    ,

    Event Hubs

    ,

    Kafka

    , and

    Azure Functions

    .
  • Validate

    Spark Streaming

    applications, including

    unbounded data flows

    ,

    streaming DataFrames

    ,

    checkpoints

    , and

    streaming joins

    .
  • Develop and execute test plans for

    containerized microservices

    deployed on

    Kubernetes

    , focusing on

    scalability

    ,

    resilience

    , and

    fault tolerance

    .
  • Test and verify

    data ingestion

    ,

    transformation

    , and

    consumption workflows

    across open table formats such as

    Delta Lake

    ,

    Apache Iceberg

    , and

    Hudi

    .
  • Collaborate with engineering and data teams to ensure

    data quality

    ,

    reliability

    , and

    compliance

    across distributed systems.

Mandatory Skills (Must Have):

  • 5 8 years of experience in

    data quality assurance

    or

    data testing

    .
  • Hands-on experience in

    real-time data streaming platforms

    Azure Service Bus

    ,

    Event Hubs

    , or

    Kafka

    .
  • Strong understanding of

    Spark Streaming

    and real-time data validation concepts.
  • Experience in

    Kubernetes-based deployments

    and

    microservices testing

    .
  • Proficiency in

    SQL

    ,

    Python

    , or any scripting language for data validation and automation.
  • Solid understanding of

    data lake architectures

    ,

    ETL pipelines

    , and

    data governance principles

    .

Good to Have Skills:

  • Experience with

    observability stacks

    such as

    Prometheus

    ,

    Grafana

    , or

    ELK

    for performance monitoring and troubleshooting.
  • Exposure to

    analytical databases and query engines

    like

    Trino

    ,

    StarRocks

    , or

    ClickHouse

    .
  • Understanding of

    data mesh architecture

    and

    domain-oriented data quality frameworks

    .
  • Familiarity with

    Azure Cloud ecosystem

    and

    CI/CD pipelines

    for data workflows.

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