Data Infrastructure Architect

Bright Vision Technologies•Wesley Chapel, FL
•$175,000 - $200,000•Remote

About The Position

Bright Vision Technologies is seeking a Data Infrastructure Architect to define and lead the architecture of its enterprise data platform across ingestion, storage, processing, governance, and consumption. The role sets the strategic direction for data infrastructure and establishes standards for data modeling and lifecycle management. The architect partners with data engineering, analytics, machine learning, and business stakeholders to deliver a coherent, scalable data foundation. The ideal candidate has deep technical expertise in modern data platforms, strong architectural judgment, and experience leading data-platform programs of meaningful scope and complexity. The position is full-time, direct W2, and 100% remote within the United States. The annual salary range is $175,000–$200,000. The employer is unable to sponsor new H-1B visa petitions; U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are encouraged to apply.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
  • Eight or more years of experience in data engineering, with significant time in architecture roles.
  • Deep expertise across at least two major data platforms, such as Snowflake, Databricks, BigQuery, or Redshift.
  • Strong understanding of lakehouse architectures, modern table formats, and streaming systems.
  • Hands-on experience with Spark, Flink, or Kafka at production scale.
  • Strong data modeling expertise across dimensional, normalized, and data-vault patterns.
  • Experience implementing governance, lineage, and catalog capabilities.
  • Solid grasp of cloud platforms, networking, identity, and cost optimization.
  • Excellent communication, facilitation, and stakeholder management skills.
  • Track record of leading large data platform initiatives across teams.

Nice To Haves

  • Experience with data mesh or data product architectures.
  • Familiarity with semantic layers such as dbt Semantic Layer, Cube, or LookML.
  • Exposure to regulated industries with strict data residency or audit requirements.
  • Cloud or platform certifications such as Snowflake, Databricks, AWS, Azure, or GCP.
  • Public talks or writing on data architecture.

Responsibilities

  • Define and lead the architecture of the enterprise data platform across ingestion, storage, processing, governance, and consumption layers.
  • Drive the strategic direction of data infrastructure.
  • Set standards for data modeling and lifecycle management.
  • Partner with data engineering, analytics, machine learning, and business stakeholders to deliver a coherent, scalable data foundation.
  • Lead large data-platform initiatives across teams.
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