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Data Engineer

Cyborg Mobile

Data Engineer

Renton, WA
Full Time
Paid
  • Responsibilities

    COMPANY OVERVIEW

    Founded in 2009, Cyborg Mobile is a human-centered consultancy providing Technology and Management Consulting Services. Cyborg Mobile provides solutions in Experience Design, Program Leadership, Organizational Change, Product Innovation, Digital Strategy, and Consumer Mobile Technology.

    At Cyborg Mobile, we use our combined expertise and empathetic approach to build products that delight customers. Our team members are passionate about growth, innovation and collaboration. We enjoy learning for fun and staying curious. If you have growth and ownership mindset and can work cohesively with a team, you are probably a great fit for our team!

    THE POSITION

    Cyborg Mobile seeks a Data Engineer to support its growing consultancy firm. This is a contract position for a public sector client of ours, with opportunity to extend into a full-time role. The key project is a data modernization effort that will help the client collect, manage, process and extract insights from data to better serve internal stakeholders and the public. This role will be part of the Data Services IT team and work closely with business analysts and SMEs.

    POSITION RESPONSIBILITIES

    As a Data Engineer, you will be responsible for all aspects of the software development lifecycle, including design, coding, integration testing, deployment and documentation. You will work in an Agile team setting to create and maintain new data applications relying heavily on experience and judgment to plan and accomplish goals.

    SPECIFIC BREAKDOWN OF RESPONSIBILITIES:

    • Analyze and resolve complex challenges around data and tools. Optimize analytical workflows by identifying opportunities and automating them
    • Collaborate with members of your team (eg, business analysts, data architect, subject matter experts) on the project's goals to understand and document business requirements
    • Translate customer requirements into unambiguous, scalable, robust and flexible technical solutions for implementation
    • Create and maintain architecture diagrams, data models, mapping documents, business rules, data flow diagrams and other design related artifacts
    • Assist the data warehouse team in designing efficient processes to load and manage data, including assessment of data quality in the source systems and implement appropriate business rules, data mappings, and transformation rules
    • Actively participate in code reviews, unit testing, system integration testing and remedy solution defects
    • Analyze and troubleshoot production issues quickly to ensure system uptime meets service level agreements

    QUALIFICATIONS/REQUIREMENTS

    • Working knowledge in data migration/integration with off-premise/cloud services such as Azure and/or AWS
    • 5+ years of experience building, administering and managing scalable analytical platforms containing both structured and unstructured data
    • Experience with Full-stack DevOps engineering—compute, network, storage and cost-optimized implementations plus application development
    • Experience working with object-oriented and scripting languages: Java, C#, Python, Javascript, etc.
    • Experience building infrastructure required for optimal ETL/ELT process for large data sets in a variety of structured and unstructured formats
    • Knowledge of big data ecosystem using tools like Hadoop, MapReduce, HBase, oozie, Flume, MongoDB, Cassandra and Pig
    • Experience working with NoSQL databases and DevOps tools: ADO, Git, Jenkins, Docker, etc.
    • Knowledge of machine learning, including pattern recognition clustering, text mining, etc.
    • Ability to work in version control and change/release management processes, alongside experience with source control mediums such as Team Foundation Server (TFS), Visual Studio Team Services (VSTS) or Git (preferred)
    • Solid understanding of data warehouse principles and multi-dimensional data modeling concepts, source to target mapping and data integration architecture. Foundational knowledge of traditional end-end ETL/OLAP solutions, preferably but not required, on the Microsoft SSIS/SSAS stack
    • Excellent written and verbal communication skills with the ability to communicate to non-technical audiences