Solutions Architect - Modern Data Management Platforms

Job Description:

Function

Product

We’re Hitachi Vantara, the data foundation trusted by the world’s innovators. Our resilient, high-performance data infrastructure means that customers – from banks to theme parks – can focus on achieving the incredible with data.

If you’ve seen the Las Vegas Sphere, you’ve seen just one example of how we empower businesses to automate, optimize, innovate – and wow their customers. Right now, we’re laying the foundation for our next wave of growth.

We’re looking for people who love being part of a diverse, global team – and who get excited about making a real-world impact with data.

We are seeking a senior Solutions Architect with 10+ years of experience designing, validating, and delivering enterprise data management solutions. This role will own the technical architecture and solution development for modern data platforms that span open table formats, object storage, lakehouse architectures, data governance, compliance‑aware architecture, streaming data pipelines, metadata services, federated query environments, and AI‑ready data foundations.

The ideal candidate is a hands‑on architect who can move fluidly between strategy, architecture, validation, and customer‑facing guidance. They should be comfortable building reference architectures, proving technical patterns in lab environments, partnering with engineering and product teams, and helping customers understand how Hitachi platforms can support governed, compliant, scalable, high‑performance data management initiatives.

Own the technical validation, architecture, and solution development of modern data management platforms for Hitachi environments, with emphasis on open, governed, compliant, interoperable, and AI‑ready data architectures.

• Open table formats, especially Apache Iceberg
• File and object storage architectures, including S3-compatible platforms
• Data lake and data lakehouse architectures
• Data governance, compliance, metadata management, lineage, and policy enforcement
• Compliance‑aware data architecture, including privacy, retention, classification, auditability, and regulatory controls
• Data preparation, ETL, ELT, and batch processing patterns
• Streaming data pipelines and real‑time data movement
• AI‑ready data foundations for analytics, RAG, and generative AI use cases
• Metadata catalogs, data catalogs, and catalog interoperability
• Federated query, data virtualization, and multi‑engine query environments
• Customer‑facing reference architectures and solution guidance for Hitachi platforms

• Design and validate end‑to‑end data management architectures that combine object storage, open table formats, query engines, governance services, compliance controls, and data pipeline technologies.
• Develop reference architectures for data lakehouse platforms using technologies such as Apache Iceberg, Parquet, Spark, Kafka, Flink, Airflow, and S3‑compatible storage.
• Build and document technical patterns for data preparation, ETL, ELT, batch processing, and streaming pipelines that support production‑grade customer deployments.
• Define architectural guidance for metadata catalogs, data lineage, data quality, data classification, PII discovery, policy enforcement, auditability, retention, and compliance operating models.
• Ensure solution architectures account for compliance requirements early in the design process, including privacy, security, regulatory alignment, data residency, retention, classification, and access governance.
• Validate interoperability between Hitachi platforms and modern data ecosystem components, including catalog services, query engines, data engineering tools, and AI data services.
• Create customer‑facing solution briefs, design guides, technical white…