Senior Data Architect

At Eneco, we're accelerating the energy transition through data and AI-driven decision-making at scale, guided by our One Planet plan and our ambition to become the first CO₂-neutral energy company by 2035. Our Data & GenAI Platforms are at the heart of this transformation, enabling product teams to deliver intelligent, secure, and compliant solutions that support the future of sustainable energy.As a Senior Architect – Data & AI Platforms, you will set the architectural vision and golden paths for Eneco’s data and AI ecosystem. You’ll work closely with Platform Engineering, Enterprise IT, and product teams to shape a scalable, interoperable, and future-proof platform landscape. In an environment that values collaboration, innovation, and continuous improvement, you will play a defining role in ensuring our platforms are trustworthy, cost-efficient, and enterprise-grade – empowering teams to innovate with confidence and speed.As a Senior Architect – Data & AI Platforms, you will own the architectural direction and evolution of Eneco’s Data & GenAI Platforms. You will define the target architecture and roadmap that enables high-velocity delivery of data, analytics, ML, and GenAI solutions while ensuring compliance, security, and efficiency.You will lead the design of a Lakehouse-centric ecosystem integrating technologies such as Databricks, Snowflake, Collibra, dbt, Airflow, and the Microsoft AI ecosystem (Copilot Studio, AI Foundry, Power Platform). A key focus will be building and scaling the GenAI platform, establishing standardized patterns for RAG, agent workflows, and LLMOps that enable product teams to rapidly deploy safe and reliable AI solutions.Through platform thinking and hands-on expertise, you’ll drive the industrialization of the modern data stack, embed governance by design, and improve developer experience through golden paths, templates, and reference architectures. You will act as a trusted advisor across the organization, coaching teams and contributing to Eneco’s strategic architecture vision.Defining and owning the target architecture and evolution roadmap for Data & GenAI Platforms, covering ingestion, transformation, orchestration, storage, serving, observability, and governance.Architecting and scaling a Lakehouse-based design interoperating with Databricks and Snowflake for analytics, ML, and serving use cases.Building and formalizing the GenAI ecosystem, including standardized RAG patterns, agent architectures, and LLMOps frameworks with strong safety and compliance guardrails.Establishing application patterns and “paved-road” templates that allow product teams to rapidly deploy AI environments and workflows.Industrializing the modern data stack with standardized dbt modeling practices and Airflow orchestration conventions.Implementing observability and FinOps monitoring for pipelines, models, cost control, quality, compliance, and performance.Operationalizing data governance through Collibra (or equivalent), embedding GDPR-compliant privacy-by-design and policy enforcement mechanisms.Ensuring interoperability with enterprise platforms, identity management, ITSM, and security standards in partnership with Platform Engineering and Enterprise IT.Leading the Architecture Community, sharing patterns, reviewing designs, mentoring teams, and driving adoption of best practices.Defining and tracking architecture success metrics such as reliability, time-to-value, cost efficiency, security, and reuse rates.10+ years of experience in data, analytics, or AI architecture, with at least 5 years leading modern cloud data platforms at scale.Deep expertise with Databricks, Snowflake, dbt, Airflow, and Collibra, including performance optimization, cost control, and governance design.Proven experience delivering GenAI and LLMOps platforms (RAG, vector search, prompt orchestration, evaluation frameworks, and guardrails), preferably on Azure.Strong knowledge of data governance, privacy and compliance (GDPR), lineage, metadata management, RBAC/ABAC, and policy-as-code.Proficiency with CI/CD and Infrastructure as Code (GitHub Actions, Azure DevOps, Terraform/Bicep) and platform SRE practices.Experience working across engineering, product, security, and enterprise IT stakeholders with strong communication and influencing skills.Deep understanding of architectural patterns such as Lakehouse, data mesh, event-driven design, CDC, and contract-first APIs.A pragmatic, solution-oriented mindset with a strategic vision for scalable, compliant platforms.Nice to have:Experience in the energy or utilities sector.Knowledge of Azure OpenAI integrations and enterprise search.Familiarity with NIS2 implications for critical infrastructure.Dutch language proficiency.You will join Eneco’s Data & AI domain, a central hub driving the company’s digital transformation and enabling smarter, sustainable energy solutions. Within this environment, you’ll collaborate closely with platform engineers, data engineers, AI specialists, product teams and enterprise IT to shape the future of Eneco’s data and AI capabilities. The culture is highly collaborative and ambitious, combining technical excellence with a strong sense of purpose: accelerating the energy transition. You’ll work in a hybrid setup from our Rotterdam office, where innovation, knowledge-sharing and continuous improvement are part of everyday practice — giving you the space to influence strategy, architecture and real-world impact at scale.Contact our recruiter at: the technical target-state:You'llbe the architect for Eneco's Data & AI platforms -designing one coherent, secure, compliant target state across Snowflake, Databricks,dbt, Airflow and Collibra. Deep technical architecture, real decision rights, zero pressure to also run the product backlog (that'sowned by Platform Owners).Our GenAI platform is evolving into an AI Product Control Plane and Agent Factory -you'lldesign the technical patterns, contracts and enforced gates that turn today's golden paths into reusable templates teams can ship agents on, safely and at scale.Make governance and data-as-a-product first-class. Design domain-aligned data products andscaffolding forend-to-end governance where GDPR, EU AI Act and J-SOX controls are inherited by design, not bolted on-closing the gap from access-control tooling to real, lineage-aware governance.