Data Architect - Singapore - ACCENTURE PTE LTD

    ACCENTURE PTE LTD
    ACCENTURE PTE LTD Singapore

    Found in: Talent SG 2A C2 - 2 weeks ago

    Default job background
    $80,000 - $150,000 per year Technology / Internet
    Description
    Roles & Responsibilities

    Job Description:

    • Lead end to end implementations of Data & ML platforms as a Project / Program lead
    • Lead engagements in defining the Data Strategy & Data Architecture for Data & ML platforms
    • Responsible for successful implementation & achievement of program objectives through leading & coordination across workstreams & dependent projects, managing risks & dependencies
    • Engage with CDO & other senior stakeholders in IT & Business to help in shaping the organization Data Strategy and Data Platform Sstrategy
    • Providing guidance & support for architecting & planning the implementation of Data & AI platforms for clients

    Job Qualifications:

    • Hands on experience with SQL, Python, Scala
    • Hands on experience with using a variety of ETL tools for data ingestion & processing
    • Led implementation of data platforms / data lakes, leveraging distributed computing frameworks to handle Data Ingestion, Processing, Serving and integration with ML Pipelines – either in cloud or on premise implementations
    • Strong understanding of the various data stores, storage formats and able to propose appropriate choices based on business needs and tradeoffs involved
    • Deep understanding of various integration patterns covering batch, near real time, real time (e.g. CDC, API, Event Streams etc), the tradeoffs with each pattern and able to provide thought leadership in determination of appropriate processing patterns
    • Conversant with upcoming & latest frameworks, tools & applicable use cases and their integration considerations into data architecture

    Good to have but not a must

    • Hands on experience with SQL, Python, Scala
    • Hands on experience with using a variety of ETL tools for data ingestion & processing
    • Led implementation of data platforms / data lakes, leveraging distributed computing frameworks to handle Data Ingestion, Processing, Serving and integration with ML Pipelines – either in cloud or on premise implementations
    • Strong understanding of the various data stores, storage formats and able to propose appropriate choices based on business needs and tradeoffs involved
    • Deep understanding of various integration patterns covering batch, near real time, real time (e.g. CDC, API, Event Streams etc), the tradeoffs with each pattern and able to provide thought leadership in determination of appropriate processing patterns
    • Conversant with upcoming & latest frameworks, tools & applicable use cases and their integration considerations into data architecture
    Tell employers what skills you have

    Scala
    Big Data
    Pipelines
    Architect
    Hadoop
    Data Management
    ETL
    Data Integration
    Data Governance
    SQL
    Python
    Data Architecture
    Data Warehousing
    Data Strategy