Data Architect/Data Modeler
Listed on 2026-07-07
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IT/Tech
Data Engineering, Data Warehousing, Business Intelligence
Location: Plano
Ascentt is building cutting-edge data analytics & AI/ML solutions for global manufacturing leaders. We turn enterprise data into real-time decisions using advanced machine learning and GenAI. Our team solves hard engineering problems at scale, with real-world industry impact. We’re hiring passionate builders to shape the future of industrial intelligence.
Job Description:Data Architect – Data & Semantic Modeling
Role Overview
We are seeking an experienced Data Architect with a strong focus on enterprise 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, building conceptual, logical, physical, and semantic models, and enabling trusted analytics across the enterprise.
This role requires a candidate who can translate business requirements into reusable data structures, define consistent business metrics, and partner with engineering, analytics, governance, and business teams to create a strong data foundation. The candidate should have hands‑on experience with modern cloud data platforms, lakehouse architecture, data warehousing, BI platforms, and governed data consumption layers.
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, lake houses, 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 Big Query, 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.
- 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.
- Strong documentation, communication, problem‑solving, and architecture leadership skills.
- Experience with semantic modeling tools or frameworks such as Power BI semantic models, AtScale, Looker, dbt Semantic Layer, Tableau semantic layer, or similar.
- Experienc…
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