Big Data Modeler

We are actively seeking a Senior Big Data Modeler with strong, hands-on experience in Data Vault 2.0 to support the data strategy of a key client. This is a mission-critical role focused on building scalable, cloud-native data architecture using modern platforms and modeling practices.

Top Primary Skills – Must-Have
✅ Data Vault 2.0 – Proven experience in real-world implementations
✅ Data Modeling – Strong in relational, dimensional, star, snowflake, normalized/denormalized models
✅ Cloud Data Platforms – Snowflake, Hive, Redshift
✅ Data Lakehouse – Experience with architecture and tools like S3, Hive, Trino, HUE
✅ Big Data Ecosystem – Strong knowledge of Hadoop/Hive/S3 integration and schema design
✅ Data Governance & Quality – Understanding of MDM, Data Dictionary, Data Mapping
✅ Data Modeling Tools – ERwin, ER/Studio, or Toad Data Modeler
✅ SQL Expertise – Ability to work with complex datasets across SQL Server, Oracle, DB2
✅ Excellent Communication – Comfortable working with cross-functional stakeholders
✅ Agile & Collaboration – Experience working in agile teams with global team alignment (including Pacific Time overlap)

Key Responsibilities

• Design enterprise-scale data models (100+ entities) for both on-prem and cloud environments
• Lead implementation of Data Vault 2.0 in cloud-native data environments
• Collaborate with business analysts, product owners, DBAs, and data engineers to translate business requirements into data models
• Define and implement data governance, data quality, and data lineage strategies
• Work with modern big data stacks: Hive, S3, Trino, HUE, Snowflake
• Develop logical and physical data models using tools like ERwin, ER/Studio, or Toad
• Apply industry best practices including Bill Inmon and Ralph Kimball methodologies
• Participate in agile ceremonies and have at least 2 hours of daily overlap with Pacific Time Zone

Qualifications

• Bachelor's or Master’s degree in Computer Science, Information Systems, or a related field
• Minimum of 12 years in data architecture and modeling
• Financial services domain experience is a strong plus
• Strong documentation and presentation skills
• Ability to lead and mentor junior data engineers and analysts