Senior Data Engineer - ERP Data Harmonization & Enterprise Data Platform

Tessera Labs

• $135K — $160K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in data engineering or related field
  • Strong SQL skills with expertise in complex joins and multi-schema environments
  • Proficiency in Python or similar programming languages for data processing
  • Hands-on experience with ETL pipeline development for structured data
  • Familiarity with enterprise systems like SAP S/4HANA and Salesforce
  • Experience with distributed data processing tools, preferably PySpark
  • Ability to work in ambiguous environments and quickly adapt to change

Responsibilities

  • Integrate and standardize structured data across various enterprise systems
  • Design and implement ETL/ELT pipelines for AI-driven data unification
  • Build logic for data transformation and validation processes
  • Analyze and document complex enterprise data schemas
  • Monitor and optimize data pipelines for high-quality delivery
  • Prepare datasets for AI platforms and apply upstream MLOps practices
  • Collaborate with FDEs and client teams to address modernization challenges

Benefits

  • Flexible remote work options available
  • Opportunity to work with cutting-edge AI technologies
  • Direct impact on enterprise-level AI automation and transformation
  • Collaborative work environment with a focus on rapid iteration
  • Strong emphasis on employee ownership and innovation
Full Job Description
Location: San Jose, CA or New York City
Remote: Considered; travel required

Role Summary

We are seeking a Senior Data Engineer to design and build scalable data solutions that harmonize enterprise data across multiple ERP ecosystems. This role focuses on integrating and standardizing data from Sage ERP, Baan / Infor LN, Oracle ERP, SaaS ERP platforms (such as NetSuite), and other enterprise systems into unified data models.

The engineer will collaborate closely with ERP functional teams, Functional Data Experts (FDEs), and product engineers to translate complex business logic into robust data transformation pipelines and canonical enterprise data models.

This role requires strong experience in SQL, Python, enterprise data modeling, and ERP data structures, combined with the ability to solve complex cross-system data inconsistencies and harmonization challenges.

Key Responsibilities

Build ERP Data Integration Pipelines

Design and develop scalable ETL/ELT pipelines to ingest and transform data from enterprise systems including:
  • Sage ERP (e.g., Sage X3, Sage Intacct, Sage 300)
  • Baan / Infor LN
  • Oracle ERP / Oracle Fusion
  • SaaS ERP platforms such as NetSuite
  • Legacy ERP and adjacent enterprise systems

Implement transformation pipelines using SQL and Python.

Implement Data Harmonization Logic

Design and maintain data harmonization frameworks that standardize enterprise datasets across systems.

Define and implement cross-system mapping rules for enterprise data domains including:
  • Customers / Business Partners
  • Vendors / Suppliers
  • Materials / Products
  • Chart of Accounts
  • Cost Centers and organizational structures
  • Financial and operational transactions

Design Enterprise Data Models

Develop canonical enterprise data models that normalize ERP data across heterogeneous systems.

Implement logical and physical models supporting:
  • Relational data platforms
  • Dimensional analytics models
  • Enterprise semantic layers

Translate Functional Requirements into Data Logic

Work closely with ERP functional teams and Functional Data Experts (FDEs) to translate business rules into technical implementations.

Convert functional requirements into:
  • SQL transformation logic
  • Python-based processing pipelines
  • Validation and reconciliation frameworks

Improve Data Quality and Governance

Implement data validation, reconciliation, and monitoring frameworks.

Identify and resolve enterprise data issues such as:
  • Duplicate master data
  • Inconsistent definitions across ERP systems
  • Incomplete or legacy datasets
  • Configuration-driven inconsistencies

Required Skills & Experience

Professional Experience
  • 5-8+ years of experience in Data Engineering, Data Integration, or Data Platform development
  • Experience working with enterprise ERP systems, such as:
    • Sage ERP platforms
    • Baan / Infor LN
    • Oracle ERP / Oracle Fusion
    • NetSuite or other SaaS ERPs
  • Experience supporting ERP transformation, migration, or multi-system integration initiatives

Technical Skills

Programming
  • Advanced SQL
  • Strong Python for data engineering workflows and pipeline development

Data Engineering
  • Experience building ETL/ELT pipelines
  • Experience processing large-scale enterprise datasets
  • Familiarity with modern data architectures and distributed processing

Data Modeling
  • Strong understanding of:
    • Relational data models
    • Dimensional models
    • Canonical enterprise data models

ERP Data Knowledge

Understanding of ERP business domains including:

Finance
  • General Ledger
  • Accounts Payable / Receivable
  • Financial transactions

Supply Chain
  • Materials and product data
  • Procurement and vendor management
  • Inventory and logistics

Enterprise Master Data
  • Customers
  • Vendors
  • Products
  • Organizational structures

Behavioral & Problem-Solving Expectations

Systems Thinking
Ability to understand complex enterprise systems and business processes, and design data solutions that work across multiple platforms.

Translating Business Logic into Technical Solutions
Capability to work with functional teams and convert business rules into scalable data transformation logic.

Data Problem Solving
Strong analytical skills to diagnose and resolve enterprise data challenges.

Collaboration
Comfortable working with cross-functional teams including engineers, ERP functional consultants, and business stakeholders.

Ownership and Execution
Ability to take ownership of complex data problems and deliver production-grade solutions that scale across enterprise environments.

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