Senior Data Engineer - ERP Data Harmonization & Enterprise Data Platform

About the role

Tessera Labs is redefining how enterprises adopt and operationalize Artificial Intelligence. Backed by Foundation Capital and led by a world-class founding team, we build multi-agent AI systems that automate complex business workflows across platforms such as SAP, Salesforce, Workday, Snowflake, MuleSoft, and more. Our mission is to bring real AI automation to the enterprise - delivering speed, precision, and measurable impact. We operate with extreme ownership, move quickly, and build at the frontier of applied AI. The Senior Data Engineer will own the design and implementation of scalable data solutions that harmonize enterprise data across multiple ERP ecosystems. This role focuses on integrating and standardizing data from complex sources into unified and reliable data structures. The hire will directly enable cross-system interoperability by building robust data transformation pipelines and canonical models. This position is critical for ensuring data consistency and trust across the enterprise landscape.

Key facts

What you'll do

Design and develop scalable ETL/ELT pipelines to ingest and transform data from enterprise systems including Sage ERP, Baan / Infor LN, Oracle ERP, SaaS ERP platforms such as NetSuite, and other legacy enterprise systems.

Implement transformation pipelines using SQL and Python to meet complex business logic and high-volume data processing requirements.

Design and maintain data harmonization frameworks that standardize enterprise datasets across disparate ERP systems and business platforms.

Define and implement cross-system mapping rules for enterprise data domains including customers or business partners, vendors or suppliers, materials or products, chart of accounts, cost centers and organizational structures, and financial and operational transactions.

Develop canonical enterprise data models that normalize ERP data across heterogeneous systems, enabling a single version of truth.

Implement logical and physical models supporting relational data platforms, dimensional analytics models, and enterprise semantic layers for downstream consumption.

Collaborate closely with ERP functional teams, Functional Data Experts (FDEs), and product engineers to translate complex business logic and functional requirements into robust technical implementations.

Translate functional requirements into SQL transformation logic, Python-based processing pipelines, and validation and reconciliation frameworks to ensure accuracy and completeness.

Implement data validation, reconciliation, and monitoring frameworks to improve data quality and governance across the enterprise.

Identify and resolve enterprise data issues such as duplicate master data, inconsistent definitions across ERP systems, incomplete or legacy datasets, and configuration-driven inconsistencies.

Support ERP modernization and migration initiatives by ensuring data continuity, integrity, and consistency during transformational projects.

Provide the data backbone for enterprise analytics, AI, and automation initiatives, enabling data-driven decision-making at scale.

Engage with technical and business stakeholders to ensure delivered solutions meet operational, compliance, and scalability standards.

Requirements

5-8+ years of professional experience in Data Engineering, Data Integration, or Data Platform development within enterprise environments.

Demonstrated experience working with enterprise ERP systems such as Sage ERP platforms, Baan / Infor LN, Oracle ERP / Oracle Fusion, NetSuite or other SaaS ERPs, and legacy enterprise systems.

Proven track record of supporting ERP transformation, migration, or multi-system integration initiatives that demand data harmonization.

Advanced SQL expertise for designing complex queries, transformations, and optimizations across large datasets.

Strong proficiency in Python for data engineering workflows, pipeline development, and automation tasks.

Experience building and maintaining ETL/ELT pipelines that handle large-scale enterprise data with reliability and performance.

Solid understanding of modern data architectures, distributed processing concepts, and integration patterns.

Strong capability in relational data models, dimensional models, and canonical enterprise data modeling to support semantic clarity.

Understanding of ERP business domains including Finance with General Ledger, Accounts Payable / Receivable, and Financial transactions, as well as Supply Chain with Materials or Products, Inventory, and Bill of Materials.

Experience working in environments requiring strict data governance, validation frameworks, and reconciliation methodologies.

Practical notes

Location: San Jose, CA or New York City

Remote: Considered; travel required

Engagement: Full-time

Hours

Full-time

Travel

Remote work is considered, but travel may be required.

Deadline

None specified.