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Data Engineer - Cloud Platform Engineering

Company: Charles Schwab & Co., Inc.
Location: Austin
Posted on: February 23, 2021

Job Description:

Your Opportunity Do you want to be part of a Data Engineering team building the next generation analytics cloud platform for a leading financial firm? At Schwab, the Data and Rep Technology (DaRT) organization governs the strategy and implementation of the enterprise data warehouse, Data Lake and emerging data platforms. The organization's mission is to drive activation of data solutions, rep engagement (Sales, Marketing, and Service) technology, and client intelligence to achieve targeted business outcomes, address data risk, and safeguard competitive position. We help Marketing, Finance, Risk and executive leadership make fact-based decisions by integrating and analyzing data. We are looking for a seasoned Cloud Platform Data Engineer who has a passion for data and the new data technology platforms that support traditional and big data analytics. As a Data Engineer for the Cloud Platform Engineering team, you will be responsible for partnering with the cloud engineering, application, architecture and Business stakeholders for the design, migration and development of the Cloud Data Warehouse (CDW) platform. This role requires someone excited to help further Schwab's data transformation journey to cloud by leveraging their technology and cloud solutions expertise. You will be working with a team of Big Data and Cloud technologists who bring a lot of energy, focus and fresh ideas that support our mission to provide value by seeing the world "Through Clients' Eyes" What you are good at

  • Designing, developing, configuring, deploying, optimizing, documenting and maintaining
    • Google Cloud Platform (Google Cloud Platform) services
      • Data storage and data processing workloads in a Google Cloud Platform based Cloud ecosystem, including enhancements and optimization
      • Monitoring services on Cloud leveraging logging and alerting
      • Job & workflow scheduling, including ESP or Control M tools
      • Python and Bash Scripting
      • Identity Access management (IAM) security for Cloud assets
        • Execution of on-premise to cloud based platform migrations
        • Operationally Support and optimize Google Cloud Platform services to meet expected SLAs.
        • Functioning as an engineering team member in an agile team environment, including supporting story creation & refinement, technical documentation, maintaining Jira and supporting scrum & status reporting in project meetings
        • Leveraging existing frameworks and standards, while contributing ideas and resolving issues with current framework owners.
        • Partnering with other technical leaders tactically to define and implement optimal solutions, working through technical and project constraints considerations
        • Engaging with Business partners and key stakeholders to help foster positive user experience
        • Analytical and critical thinking ability to build long-term scalable and performant solutions
        • Reviewing code solutions and providing peer feedback with focus on best practices
        • Partnering with architects closely to deliver appropriate technical solutions What you have
          • Bachelor of Science or equivalent in Computer Science or a related field
          • Minimum of 3-5 years' experience in Information Technology traditional and Big Data projects
          • 2+ years of hands-on experience in large scale Big Data Warehouse or Data Lake platform engineering enterprise initiatives
          • 2+ years hands-on experience with Google Cloud Platform technologies (BigQuery, GCS, DataProc, DataFusion, Cloud IAM, DLP)
          • 2+ years hands-on experience with provisioning Google Cloud Platform resources using IaC (Infrastructure-as-Code) preferably using Terraform
          • Experience working with cross functional platform, application and Business teams
          • 2+ years of experience with UNIX, JAVA, Python, BASH, Terraform
          • 1+ year hands-on experience with DevOps and CI/CD tools like BitBucket, Bamboo, Cloud build etc.
          • Experience with Splunk and other monitoring or reporting tools
          • Cloud experience specifically with data analytics services on data processing and storage solutions is critical
          • Cloud experience with either AWS or Google Cloud Platform on ML/AI solutions is preferred but not required
          • Good communication and presentation skills
          • Ability to articulate and partner successfully with Business partners and technology teams
          • Attitude that fosters a culture of collaboration and teamwork
          • Strong problem-solving and critical thinking skills - provided by Dice

Keywords: Charles Schwab & Co., Inc., Austin , Data Engineer - Cloud Platform Engineering, Engineering , Austin, Texas

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