Senior Manager – Data Architecture

Responsibilities

• Lead and develop the Data Architecture team, including data architects and modelers responsible for enterprise data design, modeling standards, and architectural direction
• Set the data architecture vision and roadmap for Circle K’s modern data platform, translating strategy into practical standards, reference architectures, and execution priorities
• Create focus and drive decisions across competing priorities, helping teams balance speed, quality, reuse, governance, and business value
• Guide source discovery and data assessment, including source system identification, data availability, freshness, latency, volume, velocity, and initial source-to-target mapping
• Define ingestion and raw layer architecture, including batch, streaming, CDC, API, and file-based patterns; raw/bronze landing schemas; and incremental load strategies
• Establish cleansed and standardized data structures, including silver layer schema design, data type standardization, format normalization, and consistent transformation patterns
• Own refined and dimensional modeling standards, including facts, dimensions, conformed dimensions, slowly changing dimensions, surrogate keys, business keys, grain definition, and referential relationships
• Design curated data products that integrate data across domains and are reusable, governed, versioned, and aligned to business consumption needs
• Influence semantic layer patterns that provide consistent business metrics, entities, hierarchies, and self-service analytics experiences
• Define reusable architecture patterns for ingestion, transformation, modeling, data products, semantic models, metadata, lineage, and quality controls
• Establish practical design review practices that improve quality and consistency without slowing delivery

• 10+ years of experience in data, analytics, enterprise architecture, solution architecture, or related technology roles
• People leadership experience leading, managing, or mentoring data architects, data modelers, or senior technical specialists
• Strong enterprise data architecture background, including architecture standards, design patterns, roadmaps, governance practices, and cross-domain solution design
• Modern data platform expertise across cloud data platforms such as Azure, Snowflake, Databricks, data lakes, data warehouses, or lakehouse architectures
• Deep data modeling experience, including conceptual, logical, physical, dimensional, and semantic modeling
• Strong knowledge of ingestion and integration patterns, including batch, streaming, CDC, APIs, and file-based data movement
• Experience with governed data products that support analytics, BI, AI/ML, data science, reporting, and operational insight use cases
• Experience with data modeling, cataloging, or governance tools;
  Erwin experience is preferred
• Strong transformation leadership with the ability to lead teams through ambiguity, modernization, operating model change, and legacy platform migration
• Excellent executive and technical communication skills, with the ability to explain tradeoffs, risks, decisions, and recommendations clearly