Data Architect

Role Overview:

We are seeking an experienced Data Architect with a strong focus on enterprise data architecture, data modeling, semantic modeling, and modern data platform architecture. The ideal candidate will have a minimum of 10 years of experience designing scalable data solutions and enabling trusted analytics across the enterprise, preferably with experience supporting manufacturing or industrial environments.

This role requires a candidate who can translate business requirements into reusable data structures, define consistent business metrics, and work closely with engineering, analytics, operations, governance, and business teams to create a strong data foundation. The role combines architecture ownership with strong data-operations, delivery, leadership, and stakeholder-management responsibilities.

Key Responsibilities:

• Design and maintain conceptual, logical, physical, and semantic data models to support reporting, analytics, operational, and advanced data use cases.
• Define scalable data modeling patterns including dimensional models, star schemas, snowflake schemas, canonical models, entity relationship models, data vault concepts, and curated consumption-layer models.
• Develop semantic models that establish consistent business definitions, KPIs, metrics, hierarchies, dimensions, and calculation logic across analytics and BI platforms.
• Work with business stakeholders to understand processes, define business terms, identify key data domains, and convert requirements into clear and governed data models.
• Partner with data engineering teams to ensure data models are accurately implemented across data pipelines, warehouses, lakehouses, and semantic layers.
• Establish standards for naming conventions, keys, relationships, metadata, data lineage, data quality rules, and modeling documentation.
• Support modern data platform architecture across technologies such as Databricks, Snowflake, Azure Synapse, Microsoft Fabric, AWS Redshift, Google BigQuery, Delta Lake, or similar platforms.
• Design models across raw, curated, and consumption layers, including bronze/silver/gold or equivalent lakehouse patterns.
• Review and optimize existing models for performance, scalability, usability, consistency, and maintainability.
• Support data product design by defining domain-aligned entities, data contracts, reusable metrics, and governed consumption models.

Required Experience:

• Minimum 10 years of experience in data architecture, data modeling, data warehousing, business intelligence, enterprise analytics, or related areas.
• Strong hands-on experience in conceptual, logical, physical, and semantic data modeling.
• Deep understanding of dimensional modeling concepts including facts, dimensions, grain, slowly changing dimensions, conformed dimensions, hierarchies, and metric design.
• Experience designing semantic layers or business consumption layers for enterprise reporting and self-service analytics.
• Strong SQL skills with the ability to validate models against source data, business rules, and reporting requirements.
• Experience with modern cloud data platforms such as Databricks, Snowflake, Azure, AWS, GCP, Microsoft Fabric, or similar.
• Experience with BI and analytics tools such as Power BI, Tableau, Looker, Qlik, or similar.
• Strong understanding of metadata management, data lineage, governance, data quality, master data, and reference data concepts.
• Ability to engage with business stakeholders, data engineers, BI developers, product owners, and governance teams.

Preferred Qualifications:

• Experience with semantic modelling tools or frameworks such as Power BI semantic models, AtScale, Looker, dbt Semantic Layer, Tableau semantic layer, or similar.
• Experience with governance and catalog tools such as Collibra, Alation, Informatica, Microsoft Purview, Unity Catalog, or similar.
• Experience with data mesh, data products, domain-driven architecture, and enterprise metric stores.
• Exposure to graph modeling, business ontology, metadata-driven architecture, or knowledge graph concepts is a plus.
• Experience supporting AI/ML or GenAI use cases through well-governed and analytics-ready data models is preferred.
• Industry experience in healthcare, manufacturing, financial services, retail, supply chain, automotive, or logistics is a plus.

Key Deliverables:

• Conceptual, logical, physical, and semantic data models
• Dimensional models and subject-area models
• Business metric and KPI definitions
• Data dictionaries and data glossaries
• Source-to-target mappings
• Entity relationship diagrams
• Data lineage and metadata documentation
• Modeling standards and best practices
• Data architecture design documents
• Curated consumption-layer design patterns

Candidate Profile:

The ideal candidate is a business-oriented data architect who can bridge the gap between business meaning, technical architecture, and execution.