Forward Deployed Engineer

This is a fully remote position, open to applicants in New York.

📋 Description

• Design and prototype architectures for data virtualization that facilitate unified, near real-time access to distributed data sources, validating feasibility, performance, and integration assumptions.

• Develop prototype-level extraction, streaming, ETL, and ELT pipelines based on API.

• Integrate distributed query and transformation engines such as Spark, Presto, and SQL-based platforms in proof-of-value (POV) environments.

• Create reference architectures and working prototypes across AWS, Azure, GCP, private cloud, and on-premises settings.

• Conduct workload and performance assessments for compute, networking, storage, and GPU-accelerated environments.

• Execute proof-of-value engagements utilizing customer and industry datasets.

• Build AI-enhanced prototypes that demonstrate RAG, automation, and agentic workflows.

• Showcase AI feasibility through hybrid and GPU-accelerated environments.

• Convert prototype results into narratives that convey both technical and business value.

• Develop lightweight models for ROI, TCO, and cost comparisons to support proof-of-value outcomes.

• Assess architectural trade-offs within defined validation efforts.

• Estimate the financial implications of GenAI and agentic AI use cases.

• Transform business requirements into prototype-level architectures.

• Facilitate discovery sessions, technical workshops, and the execution of proof-of-value initiatives.

⛳️ Requirements

• Extensive experience with data virtualization platforms such as Zetaris, Starburst, Dremio, or comparable technologies.

• Hands-on experience with modern data platforms, including Databricks, Snowflake, Teradata, and cloud-native data warehouses.

• Proficient in Spark, Presto, SQL, distributed query engines, and concepts of performance optimization.

• Experience in developing prototype-level ETL/ELT pipelines and integration workflows.

• Knowledge of API-based data integration patterns.

• Experience in hybrid, multi-cloud, and on-premises environments.

• Familiarity with enterprise infrastructure and accelerated compute platforms from vendors like Hitachi, Cisco, Supermicro, HPE, Dell, Pure, and NVIDIA.

• Understanding of principles regarding data governance, security, and access control.

• Comfortable operating within large-scale enterprise data ecosystems.

🏝️ Benefits

• Flexible arrangements that cater to your needs (dependent on role and location).