Data Modeler Architect

About Ascendion

Ascendion is a premier provider of AI-Native software engineering solutions. Our capabilities in applied AI, software engineering, cloud services, data management, experience design, and talent transformation drive innovation for Global 2000 clients. Based in New Jersey, Ascendion operates with a remote/hybrid workforce and maintains a presence in 12 countries with over 40 global offices across North America, Europe, and APAC. We are dedicated to creating technology powered by Generative AI, fostering an inclusive workforce, serving our communities, and nurturing a dynamic culture. For more details, please visit www.ascendion.com.

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Join a dynamic team of high-performing innovators who are passionate about technology and brimming with ideas. Our culture is the essence of our company, distinguishing us with its diversity and uniqueness. The way we exchange ideas, knowledge, experiences, successes, and joy empowers everyone to excel at Ascendion.

Job Description

We are seeking a highly skilled Lead/Architect to oversee data architecture assessments, target data model designs, legacy data analysis, and the modernization of the Client Data platform. This role will facilitate the migration of applications to a modern cloud-native architecture hosted on AWS. The Data Modeler will collaborate with architects, business analysts, subject matter experts, developers, QA teams, and modernization specialists to establish canonical data models, integration frameworks, data governance standards, and future-state information architecture.

Please Note: Experience in Banking Domain is Mandatory

Key Responsibilities

• Perform current-state data architecture assessments across Data Platform modules and data structures.
• Analyze source systems and define data mappings for migration and integration projects.
• Develop conceptual, logical, and physical data models for Disclosure and Work Actions modules.
• Design and maintain data models for enterprise applications and analytics platforms, including conceptual, logical, and physical structures.
• Create dimensional data models (Star Schema, Snowflake Schema) for reporting and business intelligence purposes.
• Engage with business stakeholders, architects, and data engineers to clarify data requirements.
• Establish and update data dictionaries, metadata repositories, and data lineage documentation.
• Design data models tailored for AWS-based Data Lake and Data Warehouse environments.
• Collaborate closely with ETL/ELT teams to ensure effective data integration and transformation.
• Optimize data structures for performance, scalability, and cost-effectiveness.
• Implement best practices for data governance, data quality, and master data management.
• Support data modernization and cloud migration initiatives.
• Assist development teams during sprint execution and defect resolution.
• Participate in discovery sessions, design reviews, sprint demonstrations, and stakeholder workshops.
  
  

Required Skills

• 6+ years of experience in Data Modeling and Data Architecture.
• Proficient in relational database design and normalization principles.
• Experience with PostgreSQL, Dynamo DB, and SQL Server environments.
• Background in supporting legacy modernization initiatives.
• Hands-on experience with AWS-based enterprise platforms.
• Experience in developing enterprise data dictionaries and governance documentation.
• Familiarity with Agile/Scrum delivery methodologies.
  
  

Technical Skills

• Proficiency in Data Modeling tools such as ERwin, ER/Studio, PowerDesigner, or equivalent.
• Knowledge of SQL and database performance optimization concepts.
• Experience with DB2, SQL Server, PostgreSQL, or equivalent relational database management systems.
• API and integration data modeling expertise.
• Understanding of data migration and transformation methodologies.
• Familiarity with metadata management and data lineage best practices.
• Awareness of AWS Data Services.
• Proficiency in UML, ERD, and information architecture documentation.
  
  

Key Success Factors

• Approval of target data model design
• Ensured 100% traceability between requirements and data entities
• Support in the successful modernization of Disclosure and Work Actions modules
• High-quality documentation approval
• No critical data architecture defects identified during QA and equivalence testing
  
  

Join Ascendion

Become part of a team dedicated to developing next-generation AI solutions and assisting enterprises in accelerating innovation through Generative AI.