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Quincy

    Data Product Solution Architect - Quincy, United States - PeopleServe

    PeopleServe
    PeopleServe Quincy, United States

    2 weeks ago

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    Description
    Purpose

    The Data Product Architect will embed themselves in Data Product teams and support all aspects of data ingestion, data engineering, design, data modeling, data as a service and machine learning , guiding engineers and analytics teams such that the best decisions are being made at every turn and better quality data products are produced. The primary focus of the Data Product Architect is data modeling (business, logical, and physical), identification, design, definition, transfer, and access. The person in this position will have a consistent track record of working with multifaceted stakeholders by planning, designing, deploying, and sustaining cloud and on-premise data products and solutions. Proven knowledge of data, multiple information technology and software domains is very important. Shown ability to document and communicate decisions will be a key indicator of success, as will be an appetite for innovation, change, and continuous improvement.

    Duties And Responsibilities
    • Lead the analysis, design, and implementation of a comprehensive business data product, with results that can be seamlessly expanded to address other Bank business domains
    • Embed with feature teams during early design phases to consult on data, systems architecture, and API design decisions, ensuring consistent system and data models
    • Plan, participate, design, review, and structure data design review sessions. Take accountability for ensuring all key design and compliance decisions are reviewed and approved before implementation following all data architecture guidelines set
    • Ensuring adherence to proper data design and security for new cloud data platform and data products and new enhancement features
    • Responsible for data model and schema documentation into governance systems
    • Responsible for canonical models for APIs, Event Streams, and Data as a Service
    • Participate in defining standards for data quality and creating data test and validation plans
    • Empower Data Product Squads to follow better design paths with automated quality engineering and automation
    • Represent the data products in the creation of enterprise data models and corporate data standards
    • Stay up to date on relevant technologies, plug into user groups, and understand trends and opportunities to ensure we are using the best possible data-centric techniques and tools
    • Ability to manage, coach, develop, and motivate a team of Data, API, and Quality Engineers
    • Ability to work in a cross-functional team and collaborate with multiple Data Product Squads
    • Collaborate with Data Science teams to power the machine learning platform to support modeling and serving
    • Collaborate with Solution Architects from other products, Enterprise Architects to design better data products that fit the needs of the organization
    Qualifications
    • Master's degree in computer science or technical field and master's degree in Technology and/or Business-related field; equivalent trainings/certifications/experience equivalency will be considered
    • 8 or more years of equivalent experience in relevant job or field of technology.
    • 5 or more years of equivalent experience in an advanced role or technical capacity, leading teams directly or indirectly
    • 5 or more years' experience directly responsible for guiding, training, or onboarding team members in relevant technologies, capabilities, or skills
    • Experience designing and solutioning modern data platforms and solutions
    • Strong experience creating data architecture, data models using tools like ER Studio, ERWIN etc
    • Hands-on experience with cloud-based platforms like Azure Data Stack (Azure SQL, Data Factory, Analysis Services, Databricks, Azure DevOps, Azure EventHubs, etc)
    • Customer focused and Solutions Oriented mindset
    • Exceptional problem-solving and critical thinking skills
    • Hands-on Experience with Data Streaming technologies like Kafka
    • Hands-on Experience with NoSQL databases
    • Experience with ETL tools, Databricks, SQL, SSAS and T-SQL
    • Large-scale design, implementation, and operations of OLTP, OLAP, DW, NoSQL and big data storage technologies such as SQL Server, Azure SQL, Azure SQL DW, PostgreSQL, CosmosDB, RedisCache, Azure Data Lake Store, Hadoop, Hive, MongoDB, MySQL, Neo4j, Cassandra, HBase
    • Experience with MPP architecture
    • Exceptional written and verbal communication and presentation skills
    • Leadership and teamworking skills
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