Lead Data Modeler

Job description

We are looking for a highly motivated, systems-oriented Lead Data Modeler to own the design, governance, and evolution of our data warehouse at InterSystems. This role sits at the center of our data lake / data warehouse initiative and will be responsible for defining how data is structured, understood, and used across the organization. You will work closely with Data Engineering, Sales Tech, CRM, Marketing Technology, and business stakeholders to translate fragmented legacy CRM and operational systems into a unified, scalable data model. This is a hands-on role requiring strong SQL and data analysis skills, with an emphasis on data modeling, source-to-target mapping, and cross-system reconciliation. You will not primarily build ingestion pipelines, but you will define exactly how data should flow, transform, and be represented - serving as the source of truth for all downstream analytics and applications. In addition to modeling, this role will own core aspects of data governance, user access design, user support, and internal data warehouse administration within InterSystems. **Key Responsibilities** 1. **Data Modeling & Architecture Ownership** - Design and maintain conceptual, logical, and physical data models across the data lake / warehouse. - Define canonical data definitions, relationships, and business logic across fragmented legacy systems. - Build scalable, extensible models that reduce redundancy and support analytics, reporting, and operational workflows. - Establish modeling standards, naming conventions, and documentation practices across the platform. - Continuously refine models as new data sources and use cases emerge. 1. **Source-to-Target Mapping & Data Translation** - Analyze legacy CRM and other operational datasets to understand structure, quality, and business meaning. - Define detailed source-to-target mapping logic for ingestion into the data model. - Provide clear, implementation-ready transformation specifications to Data Engineers. - Validate incoming data against expected mappings and ensure alignment with defined models. - Act as the primary owner of how legacy data translates into the unified system. 1. **Data Quality, Reconciliation & Discrepancy Resolution** - Partner with Data Engineers to identify and resolve discrepancies across systems and pipelines. - Develop frameworks for data validation, integrity checks, and consistency monitoring. - Investigate edge cases and ambiguous data definitions with SMEs and stakeholders. - Establish processes for ongoing data quality governance as the platform scales. 1. **Data Warehouse Administration** - Maintain and optimize schemas and views within the data warehouse, ensuring high performance and reliability. - Support ETL workflows, data integrity checks, and reporting pipelines. - Manage user access, roles, and data security within the warehouse environment. - Monitor query performance and optimize schemas and indexing strategies. - Maintain clear, up-to-date documentation of schemas, tables, and data flows. 1. **Cross-Functional Collaboration & Communication** - Partner with Sales, CRM, Marketing, and other stakeholders to gather and clarify data requirements. - Translate complex data structures into clear, understandable documentation for non-technical users. - Work closely with Data Engineering to ensure seamless execution of ingestion and transformation logic. - Align with internal teams to standardize definitions and avoid duplication of data efforts. 1. **Platform Growth & Governance** - Own the onboarding of new data sources into the data warehouse platform. - Define scalable patterns for integrating additional systems over time. - Establish and manage user groups, access patterns, and data consumption layers. - Contribute to long-term strategy for enterprise data architecture at InterSystems. **Short-Term Goals (0–6 months)**