Data Modeler

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) 

• Build a comprehensive understanding of existing CRM and operational data sources. 

• Develop the initial unified data model across core systems. 

• Define and document source-to-target mappings for key datasets. 

• Stand up and organize the data warehouse schema. 

• Establish user groups, access controls, and initial governance processes. 

• Partner with Data Engineering to support initial ingestion and validation pipelines. 

• Identify and resolve major discrepancies across legacy systems. 

Long-Term Goals (6–24 months) 

• Expand the data model to incorporate additional business domains and data sources. 

• Evolve the platform into a scalable, enterprise-grade data lake / warehouse. 

• Establish robust data governance, documentation, and quality monitoring frameworks. 

• Enable self-service analytics through well-structured and well-documented datasets. 

• Drive standardization of data definitions across the organization. 

• Continuously optimize performance, usability, and scalability of the platform. 

Required Qualifications 

• 5+ years of experience in data modeling, data architecture, or related roles. 

• Strong SQL skills with the ability to independently analyze complex datasets. 

• Experience designing conceptual, logical, and physical data models. 

• Experience working with databases (IRIS, PostgreSQL, or similar). 

• Strong understanding of data normalization, denormalization, and schema design trade-offs. 

• Experience defining source-to-target mappings and working with ETL/ELT processes. 

• Ability to work with ambiguous, messy legacy data and derive structured solutions. 

• Strong attention to detail and commitment to data accuracy and consistency. 

Preferred Qualifications 

• Experience working with CRM or customer data platforms. 

• Familiarity with InterSystems IRIS or similar enterprise data platforms. 

• Experience supporting data governance, access control, and data quality initiatives. 

• Proficiency in Python for data analysis or validation workflows. 

• Experience using AI tools to accelerate data analysis, mapping, and documentation. 

• Strong communication skills with the ability to work across technical and business teams 

We are an equal-opportunity employer and do not discriminate because of race, color, religion, sex, national origin, ancestry, marital status, veteran status, age, disability, sexual orientation or gender identity or expression or any other legally protected category. InterSystems is an E-Verify Employer in the United States.

InterSystems is providing a current good faith estimate of the anticipated base salary range for this position depending on a variety of factors including experience, education, skills, and performance.

Other compensation may include a discretionary annual variable target incentive.

The company also provides generous employee benefits including:

• Medical, vision, and dental insurance
• Short-term and long-term disability, and life insurance
• 401(k) Profit Sharing Contribution
• Paid Time Off and Holidays
• Parental Leave
• Tuition reimbursement

The estimated base compensation range for this role is:$126,000—$163,000 USD

About InterSystems

InterSystems, a creative data technology provider, delivers a unified foundation for next-generation applications for healthcare, finance, manufacturing, and supply chain customers in more than 80 countries. Our data platforms solve interoperability, speed, and scalability problems for large organizations around the globe to unlock the power of data and allow people to perceive data in imaginative ways. Established in 1978, InterSystems is committed to excellence through its 24×7 support for customers and partners around the world. Privately held and headquartered in Boston, Massachusetts, InterSystems has 38 offices in 28 countries worldwide. For more information, please visit InterSystems.com.

AI Disclaimer

InterSystems may use AI tools for its internal operations including administrative tasks during recruitment (e.g., organizing candidate information).  InterSystems’ approach to AI is guided by the InterSystems Responsible AI Guidelines. AI is not used to make or influence hiring decisions. All decisions are made by InterSystems employees.

Candidates may use AI for CV or interview preparation, provided materials are truthful and reflect their own experience.  AI tools and third-party transcription services must not be used during interviews or assessments.

Please note that the use of wearable technology, including any AI-related tools or other technology-connected devices (such as META or Google smart glasses and/or wearables, and/or any similar devices), is strictly prohibited during the interview and screening process with InterSystems.  Any applicant who requires a wearable device or any type of technology support during the interview process as a reasonable accommodation under the ADA or applicable state or country laws and regulations must contact the InterSystems Human Resources Department prior to attending or participating in any interview or screening process.