Principal Data Architect

BrightClaim•3409-G LLC: North Carolina WFH - Virtual, US, NC
•$210,000 - $300,000•Hybrid

About The Position

The Big Data Principal Data Architect designs and implements high-performing, scalable big data solutions. The role leads data architecture strategy and development, supports data integrity, and optimizes data management processes for performance. It also provides technical guidance to data engineering teams and keeps current with developments in big data technologies and architectures.

Requirements

  • Bachelor’s degree in Business Analytics, Computer Science, or Statistics, or a master’s degree in Data Science.
  • Proficient English language skills (C2).

Nice To Haves

  • Certified Data Management Professional – Riversand.
  • Databricks Certified Associate Developer for Apache Spark 3.0.
  • Databricks Certified Associate Developer for Apache Spark.
  • Microsoft Certified: Azure Data Engineer Associate.
  • Oracle Database 12c Certified Implementation Specialist.
  • Skills listed include accounts payable process, accounts receivable, aerospace manufacturing, Agile methodology, automotive manufacturing, banking capital markets, change management, claims management, client relations, cloud computing, collaboration tools, commercial excellence, commercial modeling, computer vision, consumer electronics, consumer packaged goods, Databricks Platform, data engineering, design thinking, electronic hardware, entertainment journalism, executive presence, and healthcare payors.

Responsibilities

  • Develop and implement data architecture strategies that support business goals.
  • Lead the design and implementation of big data solutions and data pipelines.
  • Collaborate with cross-functional teams to gather requirements and design data models.
  • Ensure data quality and integrity through data governance and data management best practices.
  • Optimize storage, processing, and retrieval performance for large-scale data sets.
  • Evaluate and recommend emerging technologies and tools for big data processing and analytics.
  • Provide technical guidance and mentorship to data engineering teams.
  • Stay current with industry trends and best practices in big data technologies and architectures.

Benefits

  • Hands-on experience, mentorship, and learning opportunities.
  • Total compensation package plus benefits; specific benefits are not listed.
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