What are the responsibilities and job description for the Data Modeler position at V-Soft Consulting Group, Inc.?
Job Title: Data Architect/Data Modeler
Key Responsibilities:
- Collaborate with stakeholders including BI developers, product owners, analysts, and leadership to define data accessibility and usability requirements for reporting and analytics.
- Communicate effectively with both technical and non-technical audiences by translating complex data concepts into clear, business-friendly language.
- Create design artifacts and support implementation processes, providing oversight to other developers working on data model implementations.
- Design and implement robust data models, define relationships between entities, and ensure normalization for extensibility in both data storage and reporting layers.
- Work closely with development teams to ensure that logical and conceptual models are accurately reflected in front-end structures such as semantic layers and cubes.
- Evaluate data architecture options and communicate trade-offs to both technical teams and business stakeholders.
- Develop and refine semantic models to support evolving business reporting needs.
- Provide thought leadership in balancing scalability, performance, and speed to market in data architecture decisions.
- Create prototypes and mockups to gather feedback and align technical solutions with business objectives.
- Map business processes to data structures, visualizing data flows throughout the organization.
- Ensure data models are designed to be flexible, scalable, and adaptable to future business requirements.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or a related discipline.
Experience & Skills:
- 5 years of experience designing conceptual, logical, and physical data models.
- Deep understanding of data normalization, dimensional modeling, and data warehousing best practices.
- Proven ability to iteratively scale and expand complex data models.
- Experience with modern cloud-based data platforms such as Snowflake, Redshift, BigQuery, or Azure Synapse.
- Hands-on experience with ETL/ELT tools including dbt, Azure Data Factory, Informatica, Talend, or Fivetran.
- Practical experience in semantic modeling within BI or AI platforms.
- Familiarity with BI tools such as Power BI, Tableau, Looker, MicroStrategy, Sigma, or ThoughtSpot.
- Knowledge of data governance principles and best practices.
