Data Governance and Modeling Engineer

Key Skills:

Roles and Responsibilities:

Data Solution Design & Modeling

• Develop Conceptual, Logical, and Physical Data Models based on business requirements and data architecture principles.
• Create data mappings, transformation rules, and maintain comprehensive metadata artifacts such as data dictionaries and business glossaries.
• Collaborate with business SMEs and data stewards to align models with business processes and terminologies.
• Define and enforce data modeling standards, naming conventions, and design patterns.
• Support the end-to-end software development lifecycle (SDLC), including testing, deployment, and post-production issue resolution.

Technical Troubleshooting & Optimization

• Perform data profiling, root cause analysis, and long-term resolutions for recurring data issues.
• Conduct impact assessments for upstream and downstream changes in data pipelines or models.
• Integrate data from various sources (APIs, flat files, databases) into Snowflake, ensuring performance and scalability.

DevOps & Operations

• Work closely with Data Engineers and Business Analysts to ensure version control, CI/CD pipelines, and automated deployments using Git, Bitbucket, and related DevOps tools.
• Ensure all data solutions are compliant with governance, security, and regulatory requirements.

Skills Required:

• Minimum 8+ years of experience in data engineering and data modeling roles.
• Proven track record with cloud-based data platforms, particularly Snowflake.
• Hands-on expertise with SQL, data integration, and warehouse performance optimization.
• Experience in Life Insurance, Banking, or other regulated industries is a strong advantage.

Skills & Competencies:

• Strong knowledge of data modeling concepts and frameworks (e.g., Kimball, Inmon).
• Deep expertise in Snowflake performance tuning, security, and architecture.
• Strong command over SQL for data analysis, transformation, and pipeline development.
• Familiarity with DevOps, CI/CD, and source control systems (Git, Bitbucket).
• Solid understanding of data governance, metadata, data lineage, and data quality frameworks.
• Ability to conduct stakeholder workshops, capture business requirements, and translate them into technical design.
• Excellent problem-solving, documentation, and communication skills.

Preferred Knowledge:

• Experience in regulated industries such as insurance or banking.
• Understanding of data risk, regulatory expectations, and compliance frameworks in financial services.

Education: