Senior Data Architect

Adaptive Biotechnologies Corp.

Senior Data Architect shaping enterprise data architecture for Adaptive Biotechnologies. Collaborating with diverse teams to enhance data usability and governance practices.

Posted 7/24/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $132,000 - $198,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data architecture, data modeling, and data integration, with a strong focus on designing reusable and governed data assets across various platforms. Proficient in collaborating with cross-functional teams to implement data solutions that enhance operational efficiency and support analytics initiatives.

Highest-signal resume keywords

Data Architecture DesignData Modeling TechniquesCloud Data PlatformsData Quality ManagementData Integration Patterns

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Hard Skills

Data ArchitectureData ModelingData IntegrationData GovernanceData QualityMetadata ManagementDimensional ModelingCanonical ModelingEvent-Driven IntegrationAPI-Driven Integration

Soft Skills

Strong CommunicationCollaborationProblem-Solving

Tools & Technologies

SnowflakeDatabricksAzureAWSGCPInformaticaDbt

Industry Keywords

Data LakesData WarehousesData EcosystemsData ProductsData Flow Diagrams

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformInformatica

About the role

Key responsibilities & impact

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.
Guide teams in designing reusable and trusted data assets that can serve multiple consumption patterns, including reporting, analytics, automation, machine learning, and AI-enabled solutions.
Provide architecture guidance during solution design, data quality investigations, platform modernization, and data integration initiatives.
Communicate architecture decisions, tradeoffs, standards, and design recommendations clearly to technical teams and senior stakeholders.
All other duties as assigned

Requirements

What you’ll need

Bachelors with 7+ (or Masters with 5+) years of relevant experience in data architecture, data modeling, data engineering, data integration, analytics architecture, or related data disciplines
Strong experience designing data architectures across operational systems, analytical platforms, data warehouses, data lakes, lakehouses, and cloud-based data ecosystems.
Deep understanding of data modeling techniques, including conceptual, logical, and physical modeling, dimensional modeling, canonical modeling, and domain-oriented modeling.
Proven ability to design trusted, governed, reusable data assets for business operations, reporting, analytics, data integration, and data product use cases.
Strong knowledge of data quality, metadata management, lineage, cataloging, master data, reference data, and access control practices.
Experience defining architecture patterns for batch, near-real-time, API-driven, and event-driven data integration.
Experience working with modern cloud and data platforms such as Snowflake, Databricks, Azure, AWS, GCP, Informatica, dbt, or similar technologies.
Ability to collaborate effectively across data engineering, application, analytics, security, governance, AI/ML, and business teams.
Strong communication skills with the ability to explain complex data concepts to senior technical and business stakeholders.
Ability to balance long-term architecture direction with practical implementation guidance.
Experience creating architecture artifacts such as data flow diagrams, domain models, source-to-target mappings, architecture decision records, and data standards documentation.

Benefits

Comp & perks

equity grant
bonus eligible