Sr. Data Modeler - Must be local

  • JS Consulting
  • Philadelphia, Pennsylvania
  • 10/25/2026
Full time Information Technology Telecommunications SQL Business Analyst

Job Description

Job Description Job Description

Job Title- Sr. Data Modeler

Project Location - Onsite in Philadelphia, PA

Duration- Fulltime

Overview: The Senior Data Modeler is responsible for designing and implementing a robust and scalable data architecture. The role will work closely with business users, business analysts, product teams, development teams, and other data professionals to define and execute a comprehensive data architecture. The data modeler will identify the current data management challenges and address data modeling, data quality and data integrity issues. The ideal candidate will have a strong understanding of data modeling best practices, metadata management and data governance. The role works with Data Governance team to ensure compliance with policies, security standards, and regulatory requirements. Also works with AI/ML engineering team to capture features and data sets required for predictive models, AI/ML use cases.

Responsibilities:

•Collaborate with business users, business analysts, product teams, data and analytics engineers and others to understand data requirements and translate them into effective and efficient data models.
•Develop conceptual, logical, and physical data models, ensuring alignment with best practices and data governance standards.
•Optimize data models for performance, scalability, and ease of use reporting.
•Define and adhere to the best practices for data modeling and naming conventions.
•Conduct gap analysis of the current data landscape and identify areas for improvement.
•Contribute to the development and maintenance of data dictionaries and metadata repositories.
•Participate in data mapping and data lineage activities to ensure data integrity and traceability during the data migration process.
•Identify and resolve data modeling issues and provide recommendations for improvements.
•Contribute to the creation of semantic layer that enables self-service analytics.
•Facilitate data model review sessions with data and analytics engineering teams and others to assess and validate the proposed data model meets the business requirements.
•Excellent written and verbal communication skills, able to facilitate and work collaboratively on analysis and design.

Requirements:
•Bachelor's degree in Computer Science, Information Technology or related field.
•10+ years of experience in architecting and building enterprise data models for both operational and analytical systems.
•5+ years of experience in data modeling tools like Erwin, ER Studio. Experience with multi-user modeling tool is preferred.
•3+ years of data architecture experience in cloud data platforms (AWS, Azure).
•Expertise in conceptual, logical, physical data modeling and normalization, de-normalization techniques.
•Established data architectures for relational and non-relational databases as well as dimensional modeling for data analytics.
•Exposure to Lakehouse Architecture, Medallion architecture, Data Fabric and Data Mesh approaches and concepts.
•Experience in integrating data models with BI tools and Data Catalogs.
•Hands on experience with cloud data platforms like Snowflake, Databricks, AWS Redshift, Azure Synapse.
•Strong proficiency in SQL, including writing complex queries for data analysis, data profiling, data validation and reconciliation.
•Analyze the structure and reverse engineer data models from various data formats like XML, JSON, AVRO, etc.,
•Familiar with ETL/ELT tools and BI tools.
•Understanding of data privacy regulations (e.g., GDPR, CCPA) and best practices for data security.
•Experience working with Agile/Scrum methodologies.
•Ability to communicate complex data architecture concepts and practices to both technical and non-technical stakeholders.
•Excellent problem-solving skills, with a proactive and solution-oriented approach.
•Stay abreast of the latest techniques and technologies relevant data modeling and cloud-based data platform.