Data Architect

• Lead data architecture practice (not just hands-on engineering or ivory tower architecture).
• Define best practices and target architecture based on business needs.
• Work with data product owners, enterprise architects, and solution architects to design scalable data solutions.
• Oversee sourcing and integration of data from legacy systems into Snowflake (and possibly Databricks/Azure Data Lake).
• Define and guide data pipeline architecture (including API layers).
• Collaborate with offshore engineering teams (APAC-based) and onshore business/architecture teams.
• Align with data governance, privacy, retention, and security requirements. Strongly prefers someone with financial experience, HC close second
• Engage with the data mesh team as producer/consumer (not directly building data products).
• Potentially hands-on with pipelines early on until team grows.

Must-Haves

• Strong data architecture experience (privacy, governance, data retention, design trade-offs).
• Background in data engineering (ideally started as a Data Engineer grew into Architect).
• Cloud experience (Azure preferred; AWS/Google Cloud Platform acceptable with adaptability).
• Snowflake expertise (primary data platform).
• Data pipeline design (performance, scalability, automation).
• Familiarity with data mesh concepts.
• Experience with TOGAF/C4 models for standardized architecture artifacts.
• CI/CD best practices for data pipelines (Terraform, IAC).

• Nice-to-Haves

• Databricks and/or Azure Data Factory exposure.
• Certifications (Azure/data-related) helpful but not required.
• Experience with high-volume/low-latency systems beneficial but not mandatory.
• Financial services industry background strongly preferred (regulated environments).