Overview
Skills
Job Details
Role: Senior Data Modeler
Locations: Jersey City, NJ (Hybrid Onsite)-Local or nearby only
Duration: 12+ Months Contract
Note: Candidate needs to be in the office 3 Days every week. Local or candidates from Nearby states only.
Must Have Skills - Investment Mgmt / Asset Mgmt domain and Experience in implementing data model using DATaVault2.0, data modeling tools, SQL, NoSQL, and other database
Required Skills & Qualifications:
- Experience: 13+ years of experience in data modeling, data architecture, or related fields.
Tools & Technologies:
- Extensive experience with data modeling tools such as Erwin, IBM Infosphere Data Architect, or Microsoft Visio.
- Proficiency with SQL, NoSQL, and other database technologies (Oracle, SQL Server, MySQL, PostgreSQL, Hadoop, etc.).
- Knowledge of cloud-based data platforms (AWS, Azure, Google Cloud Platform) and modern data warehouses (Snowflake, Redshift, BigQuery).
- Advanced Knowledge: Strong understanding of database design, normalization, denormalization, star/snowflake schemas, and ETL processes.
- Methodologies: Experience in Agile and DevOps environments.
- Data Governance & Security: Experience with data privacy, security protocols, and governance frameworks.
- Business Acumen: Strong understanding of how to align data models with business requirements, ensuring that the data architecture supports key business goals.
Job Description:
- We are seeking a highly experienced Senior Data Modeler with over 13 years of expertise in data modeling, architecture, and analytics.
- The successful candidate will play a key role in designing and optimizing data models for complex data systems across a variety of platforms.
- You will work with cross-functional teams to ensure that data is structured efficiently and is leveraged for business insights.
Key Responsibilities:
- Investment management domain knowledge
- Experience in implementing data model using DATaVault2.0
- Data Modeling: Lead the design, development, and implementation of data models (logical, physical, and conceptual) for enterprise-scale data systems.
- Data Architecture: Collaborate with the data architecture team to develop and maintain scalable and high-performance data models for reporting, analytics, and business intelligence.
- Stakeholder Engagement: Work closely with business analysts, data engineers, and other stakeholders to understand data requirements and translate them into robust data models.
- Data Governance & Quality: Ensure that data models comply with industry standards for data governance, security, and quality. Implement data quality checks and validation processes.
- Optimization & Performance Tuning: Optimize existing data models and queries for performance improvement and scalability.
- Mentorship: Provide guidance and mentorship to junior data modelers and analysts.
- Best Practices & Standards: Define and enforce data modeling best practices, standards, and guidelines for the organization.
- Documentation: Create and maintain comprehensive documentation for data models, including data dictionaries, entity-relationship diagrams (ERD), and schema definitions.
- Innovation & R&D: Stay current with industry trends and emerging technologies related to data modeling, analytics, and databases.
Shivam Kumar
Technical recruiter | Empower Professionals
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