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Location
In office
Seniority
Architect · 5+ years exp

Confirmed on the employer's own hiring board on Nov 14, 2026. First seen by Alion on Nov 13, 2026. Svitla Systems scores B on the Alion truth index.

Overview
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Svitla Systems is a software development and IT services company headquartered in Corte Madera, California. Founded in 2003, it provides custom software development, managed teams and staff augmentation covering cloud, AI and machine learning, data engineering, DevOps, QA and web and mobile applications. It has delivery centres in Ukraine, Poland, Latin America and other regions and hires developers, database administrators, data analysts, QA engineers and solution architects.

Svitla Systems Inc. is looking for a Data Platform Architect for a full-time position (40 hours per week) in the US. Our client is a specialized IT staffing and recruitment firm with decades of experience in the SAP ecosystem. The company places senior SAP professionals with leading consulting firms, global system integrators, and enterprise organizations across industries such as retail, manufacturing, and pharmaceuticals. It offers flexible engagement models, including contract, contract-to-hire, and direct placement.

As a Data Platform Architect you will support our client's continued growth. The Data Platform Architect owns the overall design of the technical solution and recommends best-practice solutions based on client needs. They provide technical guidance for the development of Salesforce and other SaaS applications in support of business and product strategies, with a strong emphasis on maximizing the Salesforce Data 360 (D360) ecosystem.

The Data Platform Architect facilitates discovery sessions to understand client processes and challenges, and translates the findings into technical requirements backed by a documented solution design. Through thoughtful leadership and clear communication with project and client team members, they build the foundation of a trusted partner relationship.

Requirements

  • 5+ years of experience in solutions architecture or technical consulting for cloud data platforms across multiple enterprise workstreams.
  • Salesforce D360 (Data Cloud) expertise: Expert knowledge of the architecture and capabilities, including the data model (DMOs, DSOs), identity resolution, data spaces, calculated insights, and activation targets.
  • Data modernization advocacy: Passion for modern data architecture methods, including lakehouse architecture, zero-copy data sharing, and real-time data activation.
  • Broad data ecosystem experience: A comprehensive range of experience in enterprise database technology, cloud data warehouses (e.g., Snowflake, Databricks), ETL/ELT tools, data engineering pipelines, and data science principles.
  • Elite communication: Strong verbal and presentation skills, with the ability to explain complex data architecture concepts to stakeholders and prospective clients at all levels of an organization.
  • Strategic roadmap leadership: Demonstrated experience leading strategy and digital roadmap projects in a complex business environment, and a proven ability to guide clients toward optimal standard solutions when initial custom designs are not a fit.
  • Technical tooling and development: Experience with data-centric programming languages (such as SQL and Python) and Salesforce application development components (Apex, Flow, LWCs, MuleSoft).
  • Advanced architecture patterns: Deep understanding of enterprise architecture patterns, API management, and real-time data streaming technologies (e.g., Kafka, Amazon Kinesis).
  • Structured data modeling: Mastery of data modeling methodologies (such as Kimball dimensional modeling, Star/Snowflake schemas, or Medallion Bronze/Silver/Gold structures) and of how they map into a canonical Customer 360 model.
  • Full-time permanent US work authorization.

Will be a plus

  • Bachelor’s degree, or equivalent experience.
  • Salesforce Certified Data Cloud Consultant or Accredited Professional designations.
  • Hands-on experience with core Salesforce CRM technology, such as Sales Cloud, Service Cloud, or Industry Clouds (e.g., Financial Services Cloud, Health Cloud).
  • Hands-on experience deploying AI/ML solutions such as Salesforce Einstein, AWS SageMaker, or Google Vertex AI, along with a solid understanding of Generative AI patterns (e.g., Retrieval-Augmented Generation, or RAG).
  • Experience designing data architectures on cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform.
  • Hands-on expertise with analytics and visualization tools such as Tableau, CRM Analytics, Power BI, or Looker.
  • Openness to travel based on client and business demands.

Responsibilities

  • Enterprise D360 harmonization: Develop and implement data architectures that align with business needs and leverage Salesforce Data 360 (D360) capabilities for unified profile management, data democratization, and real-time activation.
  • Modern cloud integration: Design and implement data solutions that bridge enterprise cloud data platforms (data lakes and warehouses) with the Salesforce ecosystem to address specific business needs, such as Business Intelligence (BI), ETL/ELT, and AI/ML.
  • Legacy migration: Assist with the migration, ingestion, and mapping of customer data from legacy systems and siloed databases into the Salesforce D360 platform.
  • Governance and trust: Ensure data accessibility, data privacy, granular security controls, and compliance with relevant regulations (e.g., GDPR, CCPA) and industry standards within the customer data ecosystem.
  • Ingestion and streaming pipelines: Design and implement real-time streaming and batch data pipelines for ingesting, transforming, and loading high-volume enterprise data into Salesforce D360 from various cloud sources and APIs.
  • D360 identity resolution: Design and implement scalable data models and metadata architectures within Salesforce D360, defining identity resolution rules, reconciliation rules, and unified data graphs.
  • Performance optimization: Monitor and optimize query performance, calculated insights, identity resolution runs, and data transformation processes within Salesforce D360 and the underlying lakehouse environment.
  • Cross-functional collaboration: Collaborate with key stakeholders, including business users, data engineers, data scientists, and CRM IT teams, to understand requirements and deliver unified data solutions.
  • Ecosystem evaluation: Evaluate and select appropriate tools, connectors, and zero-copy / zero-data-movement technologies for seamless data integration, transformation, and activation within the Salesforce D360 ecosystem.
  • Technical guidance: Provide technical leadership, architectural oversight, and best-practice guidance to data engineering and CRM development teams.
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