Senior Data Architect

Job Duration: 4 months
Sr. Data Architect (GCP/BiqQuery)
We are seeking a Senior Data Architect to design and deliver a unified Sales & Compensation dataset. The role involves creating the compensation calculation domain, producing clean and auditable datasets that downstream systems can trust and consume. The architect will work closely with an Agile Product Owner, reverse-engineer existing data logic where needed, set standards and guardrails for the data engineering team, and lead delivery of the hierarchy model first, followed by the compensation domain.

Sr. Data Architect Requirements:

• 10+ years of experience in data architecture and modeling at scale (relational, dimensional, hierarchy modeling, slowly changing dimensions, effective/bitemporal dating).
• Proven background designing financial, compensation, or pricing datasets with versioning rules and full auditability.
• Strong experience with data modeling, transformation design, orchestration, and automation.
• Deep knowledge of data governance and compliance frameworks, including security controls, metadata management, and audit processes.
• Ability to assess complex, messy legacy models and deliver a clean, optimized target design.
• Strong stakeholder communication and a product-focused mindset.

• Architect the target data model for employee and store hierarchies and the consolidated orders (compensation) domain.
• Reverse-engineer existing data logic and document the current state, leading a canonical rebuild grounded in best practices.
• Design a rule and versioning framework for compensation to support accurate historical replay and auditing.
• Define ingestion and transformation patterns, including change data capture from enterprise and legacy systems, as well as backfill strategies.
• Establish governance standards: data contracts, lineage tracking, testing, access controls, and compliance logging.
• Optimize for performance and cost efficiency, applying best practices for partitioning, clustering, caching, and workload management.
• Set standards and guardrails for development, mentor engineering teams, and partner closely with the Product Owner.
• Collaborate with business and technical stakeholders across multiple departments to ensure data models are well-documented, maintainable, and easy to consume.