Data Platform Architect
100% Remote (Continental United States)Full-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years
- Required Skills
- KafkaSnowflakeData engineeringSparkBigQueryRedshiftDatabricks
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.
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 technologies such as Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or Hudi.
- Design end-to-end data pipelines that balance latency, cost, reliability, and maintainability across batch and streaming workloads.
- Lead the 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 ensure platform capabilities align with downstream consumption needs.
- Establish data contract and data product principles to drive ownership, quality, and decoupling between producers and consumers.
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