Principal Commercial Data Architect

200 - 220 PLN/ godz./ godz.B2BB2B (netto)

SeniorZdalnie·WarszawaInne·B2B

#474773·Dodano wczoraj·0

Źródło: justjoin.it

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Tech Stack / Keywords

AWS SQL Snowflake KafkaDBT

Podsumowanie oferty

Own and evolve a scalable commercial data foundation supporting CRM, service, marketing, and commercial operations applications. Define commercial data models, integration patterns, and semantic standards using technologies including Snowflake, AWS, Kafka, DBT, and SQL.

Wymagania

Education & Experience:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related quantitative field.
12+ years of hands-on experience in enterprise data architecture, data modeling, or solution architecture, preferably within commercial, CRM, or customer service domains.
Proven experience designing data backbones or unified data layers supporting multi-application ecosystems, such as Salesforce, Veeva, SAP, or ServiceNow.

Technical & Domain Skills:

Expert proficiency in conceptual, logical, and physical data modeling, including relational, dimensional, document, and graph models.
In-depth understanding of commercial value streams across Marketing, Sales, Customer Support/Service, and Commercial Operations.
Experience with cloud data platforms such as Snowflake, AWS, or Azure Data Lake; API and event-driven architectures such as Kafka, AMQP/MQTT, REST/GraphQL; and modern data tooling such as DBT and SQL.
Ability to establish precise semantic content for AI and agentic systems, including entity and metric definitions, calculation logic, and valid interpretation scope.
Experience defining completeness criteria for data products intended for conversational consumption and recognizing how ambiguous or incomplete definitions can produce semantically incorrect answers.
Ability to explain complex architectural concepts to non-technical business stakeholders and negotiate shared technical roadmaps.

Nice to have:

Experience with Master Data Management, including HCP/HCO/Account structures.

Obowiązki

Drive the Target Data Architecture:

Architect and continuously evolve a scalable commercial data foundation serving downstream applications, including CRM, Service Desks, Marketing Automation, Order-to-Cash, and Commercial Ops.

Define Domain Models & Standards:

Create and maintain enterprise conceptual and logical data models, taxonomies, and ontologies for key commercial entities.
Apply Domain-Driven Design (DDD) to establish bounded contexts across commercial sub-domains.

Establish Integration Pathways:

Design real-time, event-driven data streaming patterns and API contracts to synchronize data between service platforms, transactional systems, and analytical data lakes and warehouses.
Apply Event-Driven Architecture (EDA) principles to support consistency and scalability while preserving system and team independence.

Establish Semantic Authority for AI-Driven Commercial Analytics:

Own the semantic content of the commercial data domain, including entity and metric definitions, calculation logic, business meaning, and permitted interpretation scope.
Contribute to standards and validation gates for determining which commercial data products are ready for conversational and agentic consumption.
Ensure semantic authority and lineage are preserved across replication, cloning, and aggregation.

Align with Enterprise AI Guardrails:

Ensure commercial data consumption complies with enterprise controls for provenance, data protection, retention, and auditability.
Ensure semantic scope and access scope are enforced consistently as data reaches AI-facing surfaces.

Architecture Governance & Decision Making:

Own and scale the ADR governance model across the Commercial data domain.
Contribute to GDRs that set metadata and semantic standards, keeping architectural decisions and governance policy consistent.
Ensure alignment with enterprise reference architectures, data security guidelines, and global healthcare compliance standards, including GxP and GDPR.

Manage Technical Debt & Modernization:

Identify opportunities to consolidate legacy data silos, reduce technical debt, and optimize the data landscape toward vendor-agnostic, future-proof patterns across multi-domain commercial environments.

Collaborate & Influence:

Partner with Product Owners, Enterprise Architects, Data Engineers, and Commercial Business Leaders to turn business capabilities into data products.

RITS

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