Location: Berkeley Heights, NJ / Carol Springs, NJ
Job Type: Contract
Salary: Competitive
Duration: Not Specified
Experience: 15+ years, data modeling, financial services
Job Description & Details
"The data landscape is evolving faster than ever, and businesses need rock\u2011solid architectures to stay competitive. As companies shift to cloud and real\u2011time analytics, seasoned data modelers are in high demand. This contract role offers a chance to shape enterprise\u2011wide data strategies for a leading financial institution.\n\n# Job Summary\nWe are seeking an expert Data Modeler to design and govern enterprise\u2011wide data architectures, build high\u2011performance operational data stores and near\u2011real\u2011time warehouses, and champion best\u2011practice standards across cloud and on\u2011prem environments. The role involves hands\u2011on modeling with tools like Erwin, advanced SQL development in Snowflake, Oracle Exadata, and MongoDB, as well as scripting in Python to automate data pipelines and governance.\n\n# Top 3 Critical Skills Table\n| Skill | Why it's critical | Mastery Level |\n|---|---|---|\n| Enterprise Data Modeling (ER, Logical, Physical, Conceptual) | Forms the backbone of reliable data assets and ensures a single source of truth across the organization. | Senior |\n| Snowflake & Data Warehousing (SQL, pipelines, stored procedures) | Enables high\u2011performance, scalable storage and analytics for near real\u2011time reporting. | Senior |\n| Python Scripting & Automation | Automates data ingestion, monitoring, and governance, reducing manual effort and error rates. | Senior |\n\n# Interview Preparation\n1. **Describe your end\u2011to\u2011end process for creating a physical data model in Snowflake, from source analysis to performance tuning.**\n **What the interviewer is looking for:** Depth of knowledge in Snowflake architecture, ability to translate business requirements into optimized tables, and experience with indexing, clustering, and query optimization.\n2. **How have you applied Kimball vs. Inmon methodologies in past projects, and why did you choose one over the other?**\n **What the interviewer is looking for:** Understanding of dimensional modeling vs. normalized enterprise modeling, and strategic decision\u2011making based on use\u2011case requirements.\n3. **Explain a scenario where you used Python to automate data quality checks or alerts. What libraries did you use and how did you integrate it with the data pipeline?**\n **What the interviewer is looking for:** Practical Python experience, familiarity with libraries like pandas, sqlalchemy, or airflow, and ability to embed automation into ETL workflows.\n4. **What challenges have you faced when implementing a Data Mesh or Domain\u2011Driven Design in a financial services environment, and how did you overcome them?**\n **What the interviewer is looking for:** Insight into modern data architectures, handling of governance, security, and cross\u2011domain data contracts.\n5. **Walk us through a data governance initiative you led, including metadata cataloging tools (e.g., Alation, Collibra) and how you ensured lineage visibility.**\n **What the interviewer is looking for:** Experience with metadata management, lineage tracking, and ability to drive adoption of governance standards.\n\n# Resume Optimization\n- Data Modeling (Erwin)\n- Kimball methodology\n- Inmon methodology\n- Snowflake pipelines\n- Oracle Exadata\n- MongoDB\n- Python scripting\n- Data Mesh\n- Data Catalog (Alation, Collibra)\n- Financial services data architecture\n\n# Application Strategy\nWhen reaching out to the recruiter, send a concise email that starts with a friendly greeting, attaches your up\u2011to\u2011date resume, and clearly highlights your top relevant skills. Explicitly reference the most important qualifications\u2014such as enterprise data modeling, Snowflake expertise, and Python automation\u2014and tie them to specific projects you\u2019ve delivered. Mention your extensive experience in the financial sector and your ability to lead data\u2011governance initiatives.\n\n# Career Roadmap\n| Current Role | Typical Experience | Core Focus | Next Position |\n|---|---|---|---|\n| Data Modeler | 15+ years, strong modeling & governance | Build enterprise data models, drive standards | Senior Data Modeler |\n| Senior Data Modeler | 5\u20117 years beyond entry, lead complex projects | Architect data warehouses, mentor juniors | Data Architecture Lead |\n| Data Architecture Lead | 3\u20115 years leading teams, cross\u2011domain design | Define data strategy, oversee Data Mesh implementations | Director of Data & Analytics |\n| Director of Data & Analytics | 8\u201110+ years, executive stakeholder management | Set enterprise data vision, manage large portfolios | VP of Data Strategy |\n"