Gainwell Technologies

Senior Principal Solution Architect

Gainwell Technologies

full-time

Posted on:

Origin:  • 🇺🇸 United States • Wisconsin

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Salary

💰 $148,500 - $212,200 per year

Job Level

Senior

Tech Stack

AWSCloudETLHadoopJavaPythonScalaSDLCSparkSQL

About the role

  • Provide thought leadership and technical direction to the data engineering team in building analytic data products
  • Understand and translate business requirements to data strategies that align with overall technology vision
  • Design, develop and enforce standards for the data storage, processing and governance across all environments
  • Work closely with enterprise and application architects to align the data engineering team to the overall company SDLC standards, practices, and data access patterns
  • Develop, document and maintain overall view of data platform architecture, data acquisition, data quality, and data retention
  • Provide formal and informal training for data engineers, platform engineers and ETL developers
  • Maintain knowledge of emerging technologies and architectures
  • Document and publish technical principles and standards, and mentor the data engineering team to incorporate them into their daily practices
  • Champion and present the technical vision to the executive team and business stakeholders

Requirements

  • 8+ years of overall experience in big data, database and enterprise data architecture, delivery and programming proficiency in a subset of Python, Java, and Scala
  • 5+ years of experience architecting, developing, releasing, and maintaining enterprise data lake platforms, building solutions on distributed processing frameworks such as Spark, Hadoop
  • 3+ years of experience implementing cloud-based systems. AWS and/or Databricks preferred
  • Strong SQL skills to create/maintain DB objects, query/load required data using data governance (e.g. business glossary, data dictionary, data catalog, data quality, master data management, etc.) and visualization tools to bring data literacy to the organization.
  • Broad knowledge of data technologies, tools, and disciplines including data modeling, dimensional models, third-normal-form structures, ETL/ELT, change data capture and slowly changing dimensions