About this role
Job Description
Role Mission:
Serve as the senior data architecture authority for DXP Data, translating business, analytics and AI priorities into secure, scalable, operable and cost-aware architecture across AWS, Snowflake, ingestion, analytics and AI. Own target architecture, domain data models, reusable patterns and governance-by-design, and guide engineering teams and partners.
Accountabilities:
- Architecture Strategy: Own the DXP Data target and reference architecture, principles, transition states and multi-year capability roadmap.
- Data Models and Products: Set direction for enterprise-aligned domain models, design semantic structures, data contracts and reusable data-product architecture supporting C360 and self-service analytics.
- Design Authority and Governance: Approve material designs, manage exceptions and architecture debt, and ensure security, privacy, quality, lineage, interoperability and operability are designed in.
- Standards and Paved Roads: Define and drive adoption of reusable patterns across ingestion, storage, modelling, serving, integration, metadata and AI-enabled data use cases.
- Business and Technology Alignment: Convert stakeholder priorities into sequenced architecture outcomes, explicit trade-offs and actionable decisions.
- Technical Leadership by Influence: Guide engineering, stewardship, analytics and vendor teams through reviews, prototypes, decision records, mentoring and knowledge transfer.
Responsibilities:
- Architecture Roadmap: Maintain current, target and transition architectures; prioritize architecture runway, modernization, decommissioning and technical-debt reduction.
- Data Product Design: Lead conceptual and logical modelling, guide physical design, and define data-product boundaries, contracts, ownership, quality and service expectations.
- Reference Patterns: Define implementable patterns for batch, CDC, streaming and file ingestion; orchestration; warehouse/lakehouse design; sharing; metadata and lineage.
- Assurance and Operability: Review material designs and changes for correctness, security, resilience, scale, observability, cost and performance before build or release commitment.
- Technology Evolution: Evaluate and prototype platform choices across AWS, Snowflake, ingestion/orchestration, open formats, semantic or knowledge layers and AI; document evidence, TCO and risks.
- Stakeholder and Team Enablement: Facilitate decisions, challenge unclear requirements, assess partner designs and uplift internal capability through reusable guidance and coaching.
Qualifications
Team Scope/ Stakeholders:
- Scope: Data architecture and governance across the DXP Data Platform and C360 ecosystem, including AWS, Snowflake, Datapipe/Airflow/Airbyte, SageMaker, metadata, analytics enablement, and evolving data and AI platform capabilities.
- Decision Rights: Approval of target/reference architecture, strategic data and solution designs, enterprise/domain modelling patterns, data-product architecture, technology recommendations, architecture standards and exceptions; escalation of material security, quality, operational, cost, or architectural risks before delivery or go-live.
- Stakeholders: DXP Data Domain Owner, Enterprise and Solution Architecture, Data Engineering, Platform Engineering, Data Quality Stewards, BI/Analytics, Data Science/AI, Business Data Owners, Infrastructure, Cybersecurity/ISO, Legal/Risk, application domain teams, and strategic partners.
- Role Boundary / Resources: Senior individual-contributor and design-authority role operating across internal and vendor-augmented teams in Singapore, Malaysia and India. Engineering leads retain people leadership, implementation delivery and Day-2 operational ownership; the architect sets direction, assures design & operational quality, and drives cross-team alignment and capability uplift.
Minimum Profile/ Track Record:
- 15+ years of relevant experience is preferred. Candidates with 12+ years may be considered where they demonstrate equivalent principal-level scope. Experience should include at least 7 years owning enterprise or domain data architecture and acting as a senior design authority in production-scale, multi-domain environments.
- Proven ownership of data-platform strategy, target and reference architecture, modernization roadmaps and architecture governance across internal and partner delivery teams.
- Deep expertise in conceptual, logical and physical data modelling, including customer/party models, dimensional and relational patterns, semantic layers, data products and data contracts.
- Strong technical fluency in cloud data-platform architecture - preferably Snowflake and AWS - and modern ingestion, orchestration, warehouse/lakehouse, open-table, metadata, lineage and self-service analytics patterns.
- Hands-on SQL and Python credibility sufficient to profile data, validate assumptions, prototype critical patterns and review implementation choices. Airflow and relevant ingestion technologies such as Airbyte, NiFi/Openflow or Glue are advantageous.
- Demonstrated ability to embed security, privacy, classification, access control, quality, resilience, recoverability, observability, cost and regulatory requirements into implementable architecture.
- Practical understanding of AI/ML and agentic use cases, including AI-ready data, semantic grounding, responsible-AI controls and secure use of enterprise data.
- Executive-level stakeholder leadership and a track record of leading through influence in vendor-augmented environments. Telecommunications or Customer 360 experience is advantageous.