Senior Data Architect

🔥 12 hours ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Adaptive Biotechnologies Corp.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2009

🏥 Healthcare

🧬 Biotechnology

⚕️ Healthcare Insurance

💰 $125M Post-IPO Debt on 2022-09

Healthcare • Biotechnology • Healthcare Insurance

Adaptive Biotechnologies Corp. is a leader in immune-driven medicine, aiming to revolutionize disease detection and treatment. By utilizing the adaptive immune system, the company develops diagnostic and therapeutic solutions powered by its innovative Immune Medicine platform. They offer clinical diagnostics, particularly in Minimal Residual Disease (MRD) testing, and engage in drug discovery and therapeutic development through adaptive immunosequencing technologies. Their biopharma services support the progression of clinical trials and the development of transformative medicines. Adaptive Biotechnologies leverages the complex biology of the immune system, decoding it to advance medical science and improve patient outcomes.

📋 Description

• 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

• 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

• equity grant • bonus eligible