Senior Data Architect, Scientific Data Platform

Agilent Technologies

. Own the discovery and access side of Agilent's scientific data platform .

Posted 9/24/2026full-timeRemote • California • United States, SpainSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and implementing scientific data discovery and access architectures, including data governance, integration patterns, and performance optimization. Proficient in building and managing data pipelines while collaborating across engineering and business teams.

Highest-signal resume keywords

Data GovernanceData Pipeline ManagementArchitectural DesignSQL ProficiencyIntegration Patterns

ATS Keywords

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Hard Skills

Software EngineeringData EngineeringArchitectureAPIsEvent-Driven IntegrationData CatalogsMetadata ManagementSQLProduction Code ReadingData Integrity

Soft Skills

CollaborationCommunicationStakeholder Engagement

Tools & Technologies

.NETC#AngularPostgreSQLSQL ServerRabbitMQKubernetesHelmS3-Compatible StorageAI Tools

Industry Keywords

Scientific DataLaboratory InformaticsRegulated Life SciencesAudit TrailCloud Integration

Tech Stack

Tools & technologies

AngularCloudDistributed SystemsGraphQLJavaKubernetesOraclePostgresRabbitMQSQLTypeScript.NET

About the role

Key responsibilities & impact

Own the discovery and access side of Agilent's scientific data platform
Define the target state and roadmap for scientific data discovery and access
Establish catalog and access behavior, service boundaries, contracts, integration patterns, and the path between them
Own and version catalog records, subgraph boundaries, data service views, and event schemas
Define authoritative systems under data governance rules
Design controlled, provenance-aware access paths for AI agents
Review integrations against contracts and participation requirements
Design modernization paths for legacy sources, including on-premises, hybrid, and cloud transitions
Set query and index performance targets
Design pipelines keeping catalogs, search indexes, and access views current, including backfill and recovery
Work directly with engineering on designs, implementation plans, and delivered work
Create decision records and diagrams and explain tradeoffs to technical and business stakeholders
Work with .NET/C#, Angular, federated GraphQL, PostgreSQL, Oracle, SQL Server, RabbitMQ, Kubernetes, Helm, Windows installers, S3-compatible storage, and scientific data formats

Requirements

What you’ll need

8+ years in software engineering, data engineering, or architecture with distributed systems
Experience with service boundaries, APIs, and event-driven integration
Experience defining architecture ahead of finalized standards and governance
Production-system architecture experience in data catalogs and metadata management, search and indexing, API or federated-query data access layers, or the data layer of a scientific, laboratory, or regulated application
SQL and execution-plan proficiency in PostgreSQL or SQL Server
Experience building and running data pipelines, including recovery and backfill
Ability to read production code in a typed language such as C#, Java, or TypeScript and build a proof of concept
Daily use of AI tools in architecture and data work, with ability to explain delegation and verification processes
Ability to work across product, engineering, and business teams without direct authority
Preferred: experience delivering data products consumed by applications
Preferred: working knowledge of catalog, search, and data access beyond owned areas
Preferred: laboratory informatics or regulated life sciences experience, including data integrity and audit trail expectations
Preferred: architecture decision records, C4 or similar diagrams, and interface contracts
Preferred: cloud integration patterns alongside on-premises deployment

Benefits

Comp & perks

Option to work remotely
Pay and benefit information available by country
Equal opportunity employment