Data Architect

At Adaptive, we’re Powering the Age of Immune Medicine.  Our goal is to harness the power of the adaptive immune system to transform the way diseases are diagnosed and treated.

As an Adapter, you’ll have the opportunity to make a difference in people’s lives. With Adaptive, you’ll create a career highlight through collaboration with bright, curious colleagues working at the apex of innovation and application.

It’s time for your next chapter. Discover your story with Adaptive.

Position Overview

We are looking to hire a Senior Data Architect to help define, mature, and scale our enterprise data architecture. This role will focus on designing trusted, well-governed, reusable, and scalable data assets that support business operations, reporting, analytics, data products, system integration, and emerging AI use cases.

The Senior Data Architect will partner with data engineering, application teams, analytics, security, governance, AI/ML, and business stakeholders to establish practical architecture standards, improve data usability, and ensure critical data sources are well-modeled, documented, discoverable, secure, and fit for purpose.

This role is critical to building a strong data foundation that enables consistent decision-making, operational efficiency, advanced analytics, and future-ready technology capabilities.

Key Responsibilities and Essential Functions

• Define and maintain data architecture standards, principles, patterns, and best practices across key business and data domains.
• Assess and rationalize critical data sources based on business value, quality, ownership, usage, sensitivity, lifecycle, and strategic importance.
• Design conceptual, logical, and physical data models that support operational systems, analytical platforms, reporting, data products, and integration needs.
• Establish reusable data structures, canonical data models, reference data patterns, and integration approaches to improve consistency across systems.
• Define architecture patterns for data ingestion, transformation, storage, consumption, sharing, retention, and lifecycle management.
• Partner with data engineering teams to translate architecture into scalable pipelines, curated datasets, data marts, reusable services, and platform-ready data assets.
• Drive standards for metadata, lineage, business definitions, data ownership, data quality rules, documentation, and data observability.
• Support governance practices by helping define how data should be classified, secured, cataloged, retained, and accessed.
• Work with application and platform teams to improve interoperability across source systems, APIs, data warehouses, data lakes, lakehouses, and cloud platforms.