Help lead the design, implementation, and evolution of our global data platform
Define the standards, blueprints, and governance models for our enterprise data architecture
Contribute directly to development, schema design, and infrastructure optimization
Ensure that all data-related systems, initiatives, and assets are aligned with the company's business goals, regulatory requirements, and long-term vision
Define and roll out domain-driven data product architecture across the enterprise
Establish standards for data contracts, schemas, SLAs, lineage, and discoverability (with DataHub)
Develop and maintain the enterprise data architecture roadmap across AWS, Snowflake, and hybrid systems
Design scalable solutions for real-time analytics, in-app data products, and AI/ML pipelines
Collaborate with data governance leads to enforce policies on PII, GDPR, CCPA, and international data residency
Work with engineering teams to enforce consistency in tools, pipelines, and naming conventions
Provide architectural leadership across global teams and mentor engineers on best practices
Requirements
12+ years in data architecture, data engineering, or related fields
At least 5+ years in an architect-level role
Strong hands-on SQL, Python, or other data centric programming language
Deep experience with AWS data stack (S3, Glue, Athena, Lake Formation, Kinesis/MSK, EMR/Trino, IAM)
Experience with Snowflake, with an understanding of migration paths to AWS-native
Knowledge of open table formats (Iceberg preferred, Delta Lake/Hudi)
Familiarity with semantic layers (Cube.dev, dbt metrics, LookML, Superset)
Strong understanding of data mesh principles and domain-driven data ownership
Data governance, compliance, and security knowledge (GDPR, CCPA, SOX)
Experience with DataHub (catalog/lineage), dbt, Tableau; Superset a plus.
Strategic thinker who can also roll up sleeves to write SQL, debug pipelines, and build POCs
Proven track record working across engineering, product, and data science teams in a global environment
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