
Lead Data Modeler
5 days ago
We are seeking a highly experienced Lead Data Modeler with deep expertise in Data Vault 2.0, VaultSpeed, and enterprise data modeling concepts. The ideal candidate will be responsible for designing scalable and maintainable data models, including Hubs, Satellites, Links, and Bridge tables. This role will act as a technical lead, managing offshore data engineering teams and providing strategic guidance and architectural consulting to senior management.
Key Responsibilities:- Design, develop, and optimize Data Vault 2.0 models (Hubs, Links, Satellites, PIT, and Bridge tables).
- Use VaultSpeed to automate and accelerate model generation and deployments.
- Provide technical leadership and direction to offshore data engineering teams under the Unison program.
- Collaborate with business analysts, data architects, and stakeholders to translate requirements into effective data models.
- Consult and advise management (e.g., Infineum leadership) on data architecture strategy, best practices, and technical decisions.
- Review, approve, and ensure consistency in data model designs and implementation across the project.
- Ensure adherence to data governance, quality, and security standards.
- Facilitate code reviews, peer mentoring, and best practice sharing within the engineering team.
- Identify and resolve data modeling and integration issues quickly and efficiently.
- Actively participate in architecture discussions, technical planning sessions, and project reviews.
Requirements
- 8+ years of hands-on experience in data modeling, especially in large-scale enterprise environments.
- Strong experience with Data Vault 2.0 methodology, including modeling of Hubs, Links, Satellites, PITs, and Bridge tables.
- Proven experience using VaultSpeed for metadata-driven automation of Data Vault.
- Proficiency in data modeling tools (e.g., ER/Studio, ERwin, or similar).
- Advanced SQL skills and understanding of relational and dimensional modeling.
- Prior experience in leading offshore/remote teams, including task delegation and performance oversight.
- Strong understanding of cloud-based data platforms (e.g., Azure Synapse, Snowflake, AWS Redshift).
- Familiarity with ELT/ETL processes and integration architectures.
- Excellent verbal and written communication skills; ability to present ideas clearly to both technical and non-technical stakeholders.
- Experience advising or consulting senior management on architectural and technical issues.
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