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

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.

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.

… lees de volledige omschrijving bij Talisman Talent.