Senior Data Architect
Indexed description
Job Duties
The Data Architect provides the technical leadership for Landmark’s AAM/UEM data platform — the layer that ingests, normalizes, and exposes oil & gas data (subsurface, drilling, well planning, production, finance, HSE) for the application layer and, increasingly, for external operators. You will own the data model, the ingestion and harmonization strategy across heterogeneous source systems, and the architectural roadmap for the AI-augmented data workflows that set the platform apart from a generic “ingest everything” data lake.
This is a deliberately technical, hands-on architecture role. It pairs day-to-day with an internal Data Platform Product Manager, who owns the “what and why” on the product and customer side, while you own the “how” on the data side. The two roles were created together so that customer outcomes and data architecture move in step rather than in opposition. You will work closely with engineers, data scientists, and domain experts, and your decisions about how the platform models and serves data will shape what the product can credibly promise.
What You Will Do
Data Architecture and Modelling
- Own the data model for the platform — the domain model, schema design, and the harmonization strategy that turns heterogeneous source data into a coherent, queryable whole.
- Set the standards for data quality, cataloguing, lineage, and governance, drawing on recognized frameworks where they help, so the platform is trustworthy enough to build products on and sell.
- Define the architectural roadmap for the data side and keep it coherent as the platform scales from internal enabler to multi-customer product.
- Design the ingestion patterns and pipelines that bring data from many engineering and operational systems into a common domain model — robustly, repeatably, and at scale.
- Lead multi-source data integration: reconciling differing schemas, identifiers, and semantics from upstream systems into something consistent and reusable. Where ontology- or meta-model-driven approaches fit, bring them to bear.
- Define the contracts and APIs through which the application layer and external customers consume platform data, and the clean handoff between the data platform and the products built on it.
- Own the architecture for AI-augmented data workflows — retrieval-augmented generation, semantic and vector search, and agentic pipelines — that make the platform’s data genuinely useful to engineers and scientists, not just stored.
- Decide where AI belongs in a data platform for upstream oil & gas, separating real, high-value use cases from buzzwords, and build the patterns the rest of the team will follow.
- Stay hands-on enough to prototype and validate these workflows yourself, using modern AI-assisted development tools as part of your daily working practice.
- Partner with the Data Platform Product Manager as a true peer — engaging with customer and roadmap trade-offs, pushing back substantively when the data model can’t support a request, and translating technical realities into product decisions.
- Provide technical leadership and credible review across the data side, and work alongside engineers, data scientists, and domain experts to raise the quality bar.
- Represent the data platform’s architectural direction in technical and product planning, and help the organization understand what the data layer can and should do.
- Master’s degree in Computer Science or a closely related STEM discipline.
- Extensive experience in data architecture — data modelling, schema design, ingestion patterns, data cataloguing, governance, and event-driven data flows.
- Demonstrated multi-source data integration experience: bringing heterogeneous data from many systems into a coherent, common domain model.
- Hands-on experience with modern cloud data platforms and tooling (e.g. Azure, Microsoft Fabric, SQL and cloud databases, vector databases, graph databases).
- Practical, shipped experience with AI-augmented data workflows — RAG, semantic and vector search, and agentic pipelines — not just evaluation or demos.
- Familiarity with oil & gas or energy data domains — subsurface, well, drilling, production, HSE, or finance data.
- Comfort with AI-assisted development tools (e.g. Claude Code, Copilot, Cursor, MCP-based workflows) in daily work.
- Direct experience with Norwegian E&P data ecosystems — DISKOS or comparable national/operator repositories — or with major operators such as Equinor.
- Experience standing up data governance frameworks or a data catalogue (e.g. DAMA-DMBOK or similar), or building out a Head of Data / Chief Data Officer function.
- Familiarity with ontology- or meta-model-driven integration approaches.
- Experience with modern agentic AI frameworks (e.g. LangChain, LangGraph, Pydantic-AI) and the patterns for putting them into production.
- Fluent Norwegian, and the ability to work credibly with both business and engineering stakeholders.
Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Minimum Qualifications: Minimum qualifications may be acquired through technical schools or equivalent related experience. Candidates having qualifications that exceed the minimum job requirements will receive consideration for higher level roles given (1) their experience, (2) additional job requirements, and/or (3) business needs. Depending on education, experience, and skill level, a variety of job opportunities might be available from the Technical Professional Software (Software Architect) - Chief
Location
Wergelandsveen 1, Oslo, , 0167, Norway
Job Details
Requisition Number: 209490
Experience Level: Experienced Hire
Job Family: Engineering/Science/Technology
Product Service Line: Landmark Software & Services
Full Time / Part Time: Full Time
Additional Locations for this position:
Compensation Information
Compensation is competitive and commensurate with experience.
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