Senior Remote AI Data Platform Engineer

Bright Vision Technologies

Wildwood (MO)

Remote

USD 135,000 - 170,000

Full time

2 days ago

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Job summary

Bright Vision Technologies is seeking an AI Data Platform Engineer to define and lead the architecture of the enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers. You will set standards for data modeling and lifecycle management and partner with data engineering, analytics, ML, and business stakeholders to deliver a scalable data foundation.

The ideal candidate combines deep technical mastery of modern data platforms with strong architectural

Qualifications

Bachelor’s or Master’s degree in CS, IS, or related field.
8+ years of data engineering experience, with architecture-focused roles.
Deep expertise across Snowflake, Databricks, BigQuery, or Redshift.
Strong knowledge of lakehouse architectures and modern table formats.
Hands-on experience with Spark, Flink, or Kafka at production scale.
Experience implementing governance, lineage, and catalog capabilities.

Responsibilities

Define the target-state architecture of the enterprise data platform, including ingestion, storage, processing, and consumption layers.
Establish standards for data modeling, schema evolution, partitioning, file formats, and storage organization.
Architect lakehouse, warehouse, and streaming patterns leveraging Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi.
Design end-to-end data pipelines balancing latency, cost, reliability, and maintainability.
Lead integration of governance, lineage, and catalog tools such as Collibra, Alation, Atlan, Unity Catalog, or DataHub.
Define security architecture including row- and column-level controls, masking, encryption, and identity-aware access patterns.
Partner with ML, BI, and product teams to align platform capabilities with downstream needs.
Establish data contract and data product principles to drive ownership, quality, and decoupling.
Lead architecture reviews and provide guidance on pipeline and warehouse design proposals.
Drive cost optimization and capacity planning across the data platform estate.
Design disaster recovery, multi-region, and high-availability strategies for critical data assets.
Mentor data engineers and architects on platform standards and emerging best practices.
Produce architecture artifacts including context diagrams, decision records, and reference patterns.
Stay current with data platform research and vendor offerings.