Principal Data Modeler

MUST HAVE minimum of 14 years of direct experience in the data field.

The Principal Data Modeler will be responsible for designing, developing, and maintaining complex OLTP and OLAP data models across multiple platforms, including Snowflake, Big Query, SQL server, PostgreSQL. He/she will work closely with data engineers, analysts, and business stakeholders to ensure our data models meet the highest standards of performance, scalability, and reliability of data systems.

The ideal candidate will possess a robust background in data engineering, showcasing expertise in cloud technologies, data architecture & modeling, data pipeline development. Essential qualifications include a bachelor's degree in technology. The role demands a high level of creativity and autonomy, along with strong delegation skills, enabling the effective distribution of tasks and responsibilities based on individual strengths and expertise. A hands-on approach to problem-solving is highly valued.

Responsibilities:

• Designing Data Models: Creating conceptual, logical, and physical data models to represent and structure the data of an organization.
• Database Management: Designing and maintaining databases to ensure they meet performance and security standards.
• Data Analysis: Analyzing data requirements and identifying data sources to integrate them into the data models.
• Collaboration: Working with business analysts, data architects, and other stakeholders to understand business needs and translate them into data models.
• Data Governance: Establishing and enforcing data modeling standards and best practices to ensure data integrity and consistency.
• Documentation: Creating and maintaining detailed documentation of data models, including data dictionaries and metadata.
• Optimization: Continuously refining and optimizing data models to improve performance and scalability.
• Mentoring: Providing guidance and mentoring to junior data modelers and other team members.
• Troubleshooting: Identifying and resolving data-related issues and discrepancies.
• Staying Updated: Keeping up with the latest trends and advancements in data modeling, architecture and database technologies.
• Implementation Support: Assisting in the implementation of data models within database management systems and ensuring their proper integration.
• Quality Assurance: Ensuring data models meet quality standards and align with organizational goals and requirements.

Qualifications (Education & Experience)

• Bachelor's degree in computer science, Information Technology, or related field (master s degree preferred).
• 8+ years of experience in data modeling, database design, or data architecture, particularly with Snowflake or other cloud-based data warehousing solutions.
• Mortgage Doman Knowledge. Ex: Knowledge of mortgage products, services, lifecycle, regulatory requirements, compliance standards etc.

Technical Skills:

• Snowflake Expertise: Proficient in Snowflake architecture, features, and best practices.
• SQL Proficiency: Strong skills in SQL for creating and managing databases, writing complex queries, and optimizing performance.
• Data Modeling Tools: Experience with data modeling tools like ERwin, ER/Studio, IBM Infosphere Data Architect or similar software.
• Cloud Platforms: Strong work experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
• ETL/ELT Processes: Knowledge of ETL/ELT processes and tools like DataStage, Talend, SSIS or similar software.
• Data Warehousing: Deep understanding of data warehousing concepts and methodologies.

Preferred Qualifications:

• Certification in Snowflake (e.g., Snowflake SnowPro Core Certification).
• Certifications in related areas like AWS Certified Solutions Architect, Google Cloud Professional Data Engineer, or Microsoft Certified: Azure Data Engineer Associate.