Data Engineer – Enterprise AI & ERP Modernization

Job Description:

Data Engineer — Enterprise AI & ERP Modernization

Location:
San Jose, CA or New York City, NY (Hybrid//3 days Onsite)

Duration:
Full time

Travel:
Required (Flexible location)

This role is critical in enabling FDEs (Forward Deployment Engineers) to deliver AI-driven ERP modernization rapidly and safely. You will directly influence:

• Migration acceleration
• Operational continuity
• Data-driven decision-making
• Enterprise-scale AI enablement

You will help build the foundation that powers enterprise AI, multi-agent automation, and cross-system modernization across highly complex landscapes.

As a Data Engineer
, you will partner closely with Forward Deployment Engineers (FDEs) to drive ERP modernization and AI-powered transformation for clients. Your focus will be on data harmonization, cross-system integration, pipeline development
, and ensuring that AI systems consume clean, consistent, and actionable data.

You will unify ERP, CRM, and financial systems, accelerate migration efforts, elevate data quality, and enable multi-agent AI workflows that automate enterprise operations and enhance decision‑making.

This role demands deeper ERP‑centric data understanding than a traditional ML data engineering role — while still requiring modern data engineering and automation skills.

Candidates strong in SAP‑specific data OR modern data engineering (with willingness to learn the other) are encouraged to apply.

• Data Harmonization:
  Reconcile, integrate, and standardize data across ERP, CRM, finance, and analytics systems.
• Pipeline Architecture:
  Design and build ETL/ELT pipelines that unify enterprise systems for AI and analytics use cases.
• Data Transformation & Validation:
  Implement logic, code, and workflows to cleanse, transform, validate, and prepare datasets.
• Schema Interpretation:
  Analyze complex enterprise schemas and map relationships across multiple platforms.
• Pipeline Reliability:
  Monitor, troubleshoot, and optimize pipelines for high‑quality, consistent delivery.

• Prepare structured data for multi‑agent AI platforms, orchestration engines, and operational intelligence workflows.
• Support FDEs and architects with data foundations needed for modernization and automation programs.

• Work directly with FDEs, Solution Architects, and client teams to solve enterprise data and integration challenges.
• Translate unclear or evolving requirements into clear, structured workflows and execution plans.
• Operate effectively in ambiguous, fast‑moving environments.

• Strong SQL expertise — ability to write complex, multi‑schema queries.
• Python (or equivalent scripting) for data processing, transformations, and automation.
• Data modeling fundamentals including normalized/denormalized structures, schema mapping, and relational modeling.
• Enterprise system familiarity — exposure to ERP (SAP S/4
  
  HANA), CRM (Salesforce), finance systems, or cloud data warehouses.
• ETL / Data Pipeline experience — building, maintaining, or optimizing workflows and data flows.
• Adaptability — comfort working with evolving requirements, fragmented systems, and real‑world enterprise data.
• AI/Analytics exposure (preferred) — supporting ML pipelines or AI‑enabled workflows.
• Enterprise data complexity handling — navigating inconsistent schemas, duplication, legacy objects, and cross‑system data issues.

• Ability to work effectively in a startup environment — proactive, resourceful, and adaptable.
• Balance engineering depth with practical execution and communication.
• Communicate clearly and concisely, with the right level of technical depth for the audience.
• Comfortable operating with incomplete requirements and evolving constraints.
• Strong reasoning skills, especially under ambiguity.
• Ability to use AI tools effectively to accelerate engineering and delivery.