Lead Data Architect

Norsk Hydro

. Architect and optimize warehouse and lakehouse solutions on Snowflake, Databricks and Azure, integrated with on-premises databases .

Posted 10/26/2026full-timeBudapest • HungarySeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in architecting and optimizing data warehouse and lakehouse solutions on Snowflake, Databricks, and Azure, with a strong focus on data modeling, CI/CD standards, and AI/ML readiness. Proven ability to lead design sessions, mentor teams, and enforce architecture standards while ensuring compliance with security and regulatory requirements.

Highest-signal resume keywords

Snowflake ArchitectureDatabricks SolutionsData Modelling ExpertiseCI/CD StandardsAI/ML Data Preparation

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringData WarehousingDimensional ModellingData VaultSQL Server ArchitectureBatch IngestionStreaming IngestionDataOpsCloud ModernizationFeature Data Versioning

Soft Skills

Influencing Without AuthorityMentoringCommunication

Tools & Technologies

AzureMicrosoft FabricUnity CatalogPurviewMLflowFeature Stores

Industry Keywords

Enterprise ArchitectureGovernance StructuresMultinational OrganizationCanonical ModelsSemantic Layers

Tech Stack

Tools & technologies

AWSAzureCloudSQLUnityVault

About the role

Key responsibilities & impact

Architect and optimize warehouse and lakehouse solutions on Snowflake, Databricks and Azure, integrated with on-premises databases
Lead conceptual, logical and physical data modelling standards using dimensional and data vault methods
Champion canonical models and metadata standards for data product reuse
Define semantic and business layers with BI and Analytics teams to enable self-service analytics
Define ingestion, pipeline, orchestration and automation patterns
Establish standards for CI/CD, infrastructure as code, testing and observability
Make data environments AI/ML-ready in collaboration with data scientists and ML engineers
Define and enforce D&A architecture standards through design reviews
Ensure solutions meet security, regulatory and Enterprise Architecture requirements
Advise teams on standard technology use, justified alternatives and prioritization of system updates
Lead design sessions, mentor architects and engineers, and communicate relevant architecture trends
Make cross-platform architecture decisions and recommend or escalate matters within governance structures

Requirements

What you’ll need

10+ years in data engineering, data warehousing or data platforms, including 4+ years as an architect or principal engineer
Deep expertise in warehouse and lakehouse architecture on modern cloud platforms, with expertise in at least two of Snowflake, Databricks and Microsoft Fabric
Strong conceptual, logical and physical data modelling skills
Experience with dimensional modelling, data vault, canonical models and semantic layers
SQL Server architecture and performance expertise
Experience modernizing on-premises estates to the cloud
Solid grounding in batch, CDC and streaming ingestion, orchestration and DataOps
Experience preparing data environments for AI/ML, including feature data, versioning and reproducibility
Ability to influence leaders, architects and engineers without formal authority
Experience in a large, multinational or matrix organisation
Nice to have: streaming platforms, Unity Catalog, Purview, MLflow, feature stores, FinOps awareness and AWS experience

Benefits

Comp & perks

Flexible work environment/home office
Freedom to be creative and learn from experts
Possibility to grow with the company
Opportunity to gain new certificates
Attractive benefit package
Diverse, global teams
Equal opportunities