AI Data Platform Engineer

📋 Description

• Define target-state architecture for enterprise data platform (ingestion, storage, processing
• Set technical standards for data modeling, schema evolution, partitioning, file formats, storage
• Architect lakehouse, warehouse, and streaming solutions (Snowflake, Databricks, BigQuery, Redshift
• Design end-to-end batch and streaming pipelines balancing performance, latency, reliability, cost
• Lead integration of data governance, lineage, cataloging, and discovery
• Define security architectures (identity-aware access, encryption, masking, row/column-level

🎯 Requirements

• Bachelor’s or Master’s in CS, IS, or related discipline.
• 8+ years in data engineering with architecture/platform experience.
• Deep expertise with two major data platforms (Snowflake, Databricks, BigQuery, Redshift).
• Strong understanding of lakehouse architectures, table formats, distributed processing, and
• Production-scale experience with Spark, Flink, or Kafka.
• Strong data modeling across dimensional, normalized, and data vault models.

🎁 Benefits

• Competitive salary: $135,000–$170,000 annually.
• Remote flexibility: 100% remote within the United States.
• Employment type: Full-time, direct W-2.
• Career growth: shape enterprise-scale data architecture and influence major initiatives.
• Technical impact: work across modern cloud data platforms, governance, and data products.
• Leadership: mentor engineers and establish architectural standards.