Data Architect / Data Engineering Lead, Finance

What you'll do

• Lead the design of scalable, reliable, and governed data solutions across ingestion, transformation, and consumption layers.
• Translate business requirements into robust technical designs and enterprise data architecture patterns.
• Establish and enforce production-grade engineering principles including idempotency, observability, lineage, and automated validation.
• Define standards for pipeline design, naming conventions, error handling, and deployment readiness.
• Design data quality and validation strategies across Bronze, Silver, and Gold layers.
• Manage mapping, reference, and master data as governed entities rather than hardcoded logic.
• Mentor data engineers by conducting solution design reviews, code reviews, and implementation checkpoints.
• Communicate architecture options, risks, and tradeoffs clearly to business and IT stakeholders.

What we're looking for

• Minimum of 8 years of experience in enterprise data architecture, data engineering, and lakehouse implementation.
• Minimum of 5 years of hands-on experience with Databricks, Delta Lake, PySpark, SQL, and modern cloud data platforms.
• Minimum of 5 years of experience designing and governing production-grade data pipelines with idempotency, restartability, and auditability.
• Minimum of 4 years of experience with mapping data, reference data, master data, and data standardization in complex enterprise environments.
• Bachelor's degree or equivalent (minimum 12 years work experience).
• Ability to lead design discussions, mentor developers, and influence implementation quality.
• Strong understanding of Bronze/Silver/Gold architecture, medallion patterns, data modeling, and data governance.
• Experience with Unity Catalog, Databricks Workflows, and cloud platforms like Azure, AWS, or GCP (preferred).