Senior Data Platform Architect — Remote

Bright Vision Technologies

East Brunswick Township (NJ)

Remote

USD 100,000 - 175,000

Full time

3 days ago

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Job summary

Bright Vision Technologies is seeking a Data Platform Architect to define and lead the architecture of our enterprise data platform, spanning ingestion, storage, processing, governance, and consumption layers. The role sets standards for data modeling and lifecycle management and partners 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 Computer Science, Information Systems, or a related field.
12+ years of experience in data engineering with architecture roles.
Deep expertise across at least two major data platforms such as Snowflake, Databricks, BigQuery, or Redshift.
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.

Responsibilities

Define the target-state architecture of the enterprise data platform across 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 using Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi.
Design end-to-end data pipelines balancing latency, cost, reliability, and maintainability.
Lead governance, lineage, and catalog tool integration (Collibra, Alation, Atlan, Unity Catalog, DataHub).
Define security architecture including row- and column-level controls, masking, and identity-aware access.
Partner with ML, BI, and product teams to align platform capabilities with downstream needs.
Establish data contract and data product principles for ownership and decoupling.
Lead architecture reviews and guide pipeline/warehouse proposals across teams.
Drive cost optimization and capacity planning across the data platform estate.
Design disaster recovery, multi-region, and high-availability strategies.
Mentor engineers on platform standards and best practices.
Produce architecture artifacts and stay current with data platform developments.