Domain Architect – Data Management & Analytics (Den Bosch/Hybrid)

Wat je gaat doen

Domain Architect – Data Management & Analytics (Den Bosch/Hybrid)

Practical:

Location: 's-Hertogenbosch (Hybrid working options available)

Hours per week: 32 – 40 hours

Duration: 6 months (with possibility of extension)

Start Date: November 16, 2026

End Date: May 31, 2027

Contract Type: Freelance / Interim

Hourly Rate: €90 – €108 per hour

About the Role

For a leading organization in the energy sector, we are looking for an experienced Domain Architect – Data Management & Analytics. In this role, you will help move the data and analytics landscape forward as the organization evolves from a centralized data warehouse toward a distributed, functional data mesh.

You will architect how data products are modeled, governed, delivered, and consumed across various business domains — from raw data ingestion through to executive reporting and AI-driven use cases.

This is a hands-on architecture role: you will set technical direction, evaluate and document trade-off decisions, and mentor engineering teams to implement them reliably in production.

Key responsibilities

• Target Data Architecture: Jointly define the target data architecture, covering data-product ownership, domain boundaries (DDD-style bounded contexts), and a clear layering strategy (raw → conformed → curated).
• Data Modeling & Pragmatic Hybrids: Design and evolve data models, balancing choices between Data Vault 2.0 (for integration, auditability, and source decoupling), dimensional/Kimball marts (for performance and usability), and other patterns. Implement pragmatic hybrids including Business Vault optimization, PIT/Bridge tables, hash-key standards, conformed dimensions, and late-arriving/multi-active data handling.
• Semantic Models & Power BI: Design semantic models for Power BI consumption on top of governed Snowflake/dbt data products (fact granularity, conformed vs. local dimensions, canonical KPI measures, Row-Level Security, incremental refresh, and promotion/versioning rules for self-service analytics).
• Security & IAM Patterns: Define identity, access, and security patterns for data processing workloads: workload/service identities (IAM roles, OIDC federation), key-pair authentication for BI tooling, least-privilege role structures, and PII/governance controls.
• Testing & Dataflow Strategy: Define and improve dataflow testing strategies and implementations, focusing on the separation between test and production environments and enabling effective non-production test data.
• Lineage & Observability: Extend architecture into lineage and observability, enabling end-to-end impact analysis from source system changes down to downstream data products across mixed modeling styles.
• AI & Advanced Analytics: Shape compliance-first, business-context-aware data access patterns so AI applications and agentic use cases receive traceable, governed, quality-gated data rather than ad hoc shortcuts.
• Architecture Governance & Mentorship: Produce clear architectural artifacts (Architecture Decision Records, governance matrices, onboarding guides, and standards) while mentoring data engineers, analytics engineers, and BI developers around shared conventions.

Wie ben jij?

Candidate profile

• Data Mesh & Domain Platforms: Proven track record architecting data mesh or domain-oriented data platforms, including data-product ownership and distributed governance models.
• Hands-on Data Modeling & dbt: Deep hands-on expertise with data modeling and dbt (modeling patterns, data testing, dbt contracts, and performance tuning such as clustering keys and materialized views).
• Pragmatic Architecture Mindset: Strong grasp of modeling trade-offs across Data Vault 2.0, Kimball/dimensional modeling, One Big Table (OBT), and normalized approaches — knowing precisely when and how to combine them.
• Power BI & Semantic Layer: Extensive experience designing semantic models and governed self-service analytics in Power BI (experience with Microsoft Fabric is a strong plus).
• Lineage & Observability: Practical understanding of data lineage and impact-analysis concepts across heterogeneous modeling layers.
• Communication & Stakeholder Alignment: Outcome-driven approach with the ability to clearly articulate the business and technical rationale behind architectural choices.
• Bonus / Preferred: Experience architecting AI/LLM context layers that responsibly expose governed enterprise data to AI applications and agents.

Het aanbod

Apply

1. Introduction with Recruitment: You start with a conversation with our recruiter to discuss your experience, ambitions, and fit with the vacancy.
2. Presentation to the client: After a positive introduction, we submit your profile to the client.
3. Client interview: If the client invites you, the interview takes place. Our account manager is either present for the introduction or contacts you beforehand. Depending on the client, this is one or two interviews, online or on-site.
4. Finalization and start: If there is a successful match, we arrange the contractual matters so you can start your new role without worries.

Contact

Komal Gupta

• E-mail: komal.gupta@talisman-software.nl
• Phone: 0686886779
• LinkedIn: linkedin.com/in/komalgg