Forward Deployed Engineer

Hitachi

. design and prototype data virtualization architectures enabling unified, near real-time access to distributed data sources for validating feasibility, performance, and integration assumptions.

Posted 5/16/2026full-timeRemote • New York • 🇺🇸 United StatesMid-LevelSenior💰 $125,000 - $270,000 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformSparkSQL

About the role

Key responsibilities & impact

design and prototype data virtualization architectures enabling unified, near real-time access to distributed data sources for validating feasibility, performance, and integration assumptions.
build prototype-level API-based extraction, streaming, ETL, and ELT pipelines.
integrate distributed query and transformation engines such as Spark, Presto, and SQL-based platforms in POV environments.
create reference architectures and working prototypes across AWS, Azure, GCP, private cloud, and on-premises environments.
perform workload and performance evaluations for compute, networking, storage, and GPU-accelerated environments.
execute proof-of-value engagements using customer and industry datasets.
build AI-driven prototypes showcasing RAG, automation, and agentic workflows.
demonstrate AI feasibility using hybrid and GPU-accelerated environments.
translate prototype outcomes into technical and business value narratives.
build lightweight ROI, TCO, and cost comparison models to support POV outcomes.
evaluate architectural trade-offs within bounded validation efforts.
estimate financial impact of GenAI and agentic AI use cases.
translate business requirements into prototype-level architectures.
lead discovery sessions, technical workshops, and POV execution.

Requirements

What you’ll need

strong experience with data virtualization platforms such as Zetaris, Starburst, Dremio, or equivalent technologies.
hands‑on exposure to modern data platforms including Databricks, Snowflake, Teradata, and cloud‑native data warehouses.
proficiency with Spark, Presto, SQL, distributed query engines, and performance optimization concepts.
experience building prototype‑level ETL/ELT pipelines and integration workflows.
knowledge of API‑based data integration patterns.
experience working in hybrid, multi‑cloud, and on‑prem environments.
familiarity with enterprise infrastructure and accelerated compute platforms from vendors such as Hitachi, Cisco, Supermicro, HPE, Dell, Pure, and NVIDIA.
understanding of data governance, security, and access control principles.
comfort operating within large‑scale enterprise data ecosystems.

Benefits

Comp & perks

flexible arrangements that work for you (role and location dependent)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

data virtualizationAPI-based extractionETLELTSparkPrestoSQLperformance optimizationdata integrationROI modeling

Soft Skills

leadershipcommunicationcollaborationproblem-solvinganalytical thinkingtechnical workshop facilitationnarrative translationdiscovery session leadership