Data Architect

Position Overview

The Data Architect will define and lead the enterprise data architecture for Cordance Commerce, with primary responsibility for unifying reporting platforms, data models, and analytics capabilities across Solutions, Secure Retail, Upright, and Pearl Dive. This is a hands-on technical leadership role for someone who can turn fragmented operational data and customer-specific reporting into a scalable, governed, and reliable data platform.

The role partners closely with Database Administrators, Business Intelligence professionals, Engineering, Product, Finance, Customer Success, and business leaders. The Data Architect will establish a practical migration strategy that separates analytical workloads from transactional systems, protects product performance, preserves critical customer reporting, and enables a trusted source of data across the portfolio.

Key Responsibilities

• Own the target-state data architecture and roadmap for a unified reporting and analytics platform across Cordance Commerce products.
• Assess current transactional databases, data pipelines, reporting tools, standard BI reports, and customer-specific reports; document dependencies, duplication, performance risks, and migration constraints.
• Define a shared enterprise data model, canonical business definitions, master-data strategy, and system-of-record ownership for core entities such as customer, item, store, employee, transaction, inventory, donation, processing, and e-commerce activity.
• Design the separation of transactional and analytical workloads using fit-for-purpose patterns such as a cloud data warehouse or lakehouse; evaluate platforms including Snowflake and recommend the appropriate solution based on scale, security, cost, operability, and business needs.
• Create the phased migration strategy for consolidating reporting from Solutions, Secure Retail, Upright, and Pearl Dive while maintaining business continuity and customer commitments.
• Develop patterns and standards for data ingestion, transformation, orchestration, semantic models, APIs, data quality, lineage, metadata, retention, archival, and observability.
• Partner with BI professionals to rationalize the Solutions standard report catalog and reduce the support burden created by hundreds of Secure Retail customer-specific reports through reusable datasets, governed self-service analytics, and configurable reporting patterns.
• Guide DBAs and engineering teams on database architecture, PostgreSQL and Microsoft SQL modernization, replication or change-data-capture patterns, performance isolation, backup, recovery, and operational readiness.
• Establish data governance practices covering data ownership, access controls, privacy, security, auditability, quality thresholds, and change management.
• Lead technical discovery, architecture reviews, proofs of concept, and vendor evaluations; translate findings into actionable designs, sequencing, estimates, risks, and investment recommendations.
• Provide hands-on technical guidance to delivery teams, review implementation designs, and ensure new product capabilities align with the target architecture instead of creating additional data silos.
• Enable trusted enterprise dashboards and cross-product reporting that support operational, customer, financial, and executive decision-making.

Competencies:

• Enterprise Data Architecture: Converts complex, fragmented data estates into pragmatic target-state architectures and phased roadmaps.
• Technical Depth: Designs modern warehouses or lakehouses, dimensional and relational models, pipelines, semantic layers, and reporting platforms.
• Business Translation: Connects architecture decisions to customer value, product performance, operational efficiency, and measurable business outcomes.
• Data Governance: Establishes clear ownership, definitions, lineage, quality, security, and lifecycle controls without creating unnecessary bureaucracy.
• Migration Leadership: Plans incremental transitions that protect customer reporting and production stability while retiring duplication and technical debt.
• Influence and Collaboration: Builds alignment across DBAs, BI, Engineering, Product, Customer Success, and executive stakeholders.
• Ownership: Drives decisions through implementation, manages ambiguity, and remains accountable for platform adoption and results.
• AI and Analytics Readiness: Designs governed, reusable data foundations suitable for advanced analytics and AI-enabled workflows.

Required Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Management, or a related field, or equivalent practical experience.
• 8+ years of experience in data engineering, database architecture, analytics engineering, or business intelligence, including 3+ years in a data architecture or senior technical leadership role.
• Demonstrated experience designing enterprise data warehouses, lakehouses, or analytical platforms and migrating data from multiple operational systems.
• Strong data-modeling expertise across conceptual, logical, and physical models, including dimensional modeling and normalized transactional designs.
• Hands-on proficiency with SQL, relational databases, ETL/ELT patterns, orchestration, data quality, metadata, lineage, and BI semantic models.
• Experience separating reporting workloads from high-volume transactional systems and designing for performance, resilience, scalability, and cost control.
• Experience with cloud data platforms and modern data integration patterns, including APIs, replication, and change data capture.
• Strong written and verbal communication skills, including the ability to present architecture decisions and tradeoffs to technical and non-technical audiences.

Preferred Qualifications

• Hands-on experience with Snowflake and at least one major cloud platform such as AWS, Azure, or Google Cloud.
• Experience with PostgreSQL and Microsoft SQL, including modernization or migration initiatives.
• Experience consolidating reporting platforms following acquisitions or across a multi-product SaaS portfolio.
• Experience rationalizing large libraries of standard and customer-specific reports and enabling governed self-service analytics.
• Familiarity with retail, point-of-sale, inventory, e-commerce, donation, or thrift/resale data domains.
• Knowledge of data privacy, security, role-based access, audit, retention, and compliance practices.
• Experience enabling machine learning, generative AI, or agentic AI use cases through governed enterprise data products.
• Relevant cloud, Snowflake, data-management, or architecture certification is a plus.

What We Offer

• Work with a mission-driven team building impactful software solutions for the thrift and resale industry.
• Opportunity to shape shared technology capabilities across a growing portfolio of commerce products.
• Collaborative culture that values innovation, accountability, continuous learning, and transparency.
• Competitive compensation, benefits, and opportunities for career growth.

Success Measurements

Architecture & Roadmap

• Completes an agreed current-state assessment and target-state architecture covering all Commerce reporting platforms and critical data domains.
• Delivers an approved, sequenced migration roadmap with clear dependencies, costs, risks, and ownership.

Unified Data & Reporting

• Establishes common business definitions and governed data models that are adopted by reporting and product teams.
• Reduces duplicated datasets and one-off reporting solutions while preserving priority customer capabilities.
• Enables reliable cross-product operational and executive reporting from trusted data sources.

Performance, Reliability & Quality

• Moves resource-intensive analytics away from transactional systems where appropriate and measurably reduces reporting-related production impact.
• Implements measurable data-quality, freshness, lineage, observability, and recovery standards for critical data products.

Migration & Adoption

• Achieves agreed migration milestones without material disruption to customer reporting or operational workflows.
• Builds strong adoption among DBAs, BI professionals, engineers, business users, and product stakeholders.

Governance & Cost Effectiveness

• Establishes accountable data ownership and access controls for priority domains.
• Provides transparent platform usage and cost metrics and demonstrates progress toward a scalable, supportable reporting model.