Data Forward Deployed Engineer – Applied Data & ML Engineering

The role

You will work directly with enterprise clients to turn fragmented, multi-system data into trusted data products and production ML models. You will build pipelines and data models, and feed reusable patterns back into the Tessera platform.

What you will do

• Embed with client teams to scope data and ML problems and deliver working outcomes in weeks
• Own delivery quality, including validation, reconciliation to source and stakeholder sign-off
• Turn repeated client patterns into reusable components for the Tessera platform
• Design and develop scalable ETL/ELT pipelines using SQL, Python and dbt across ERP, CRM, HCM and finance systems
• Design canonical enterprise data models and cross-system mapping rules
• Implement validation, reconciliation and monitoring to resolve duplicate, inconsistent and legacy data
• Engineer features and build models for use cases such as forecasting and anomaly detection
• Deploy models to production and monitor them

Required qualifications

• 5+ years of experience in Data Engineering, ML Engineering or Applied Data Science
• Enterprise data harmonization, migration or analytics experience across ERP, CRM or finance systems
• Experience in client-facing, consulting or forward-deployed roles
• Advanced SQL and strong Python for data pipelines and ML workflows
• Experience building ETL/ELT pipelines and processing large-scale enterprise datasets
• Relational and dimensional data modeling
• dbt for transformation, testing and documentation
• Cloud platform experience (AWS, GCP or Azure)
• At least one ML model built, deployed and monitored in production on business data
• Feature engineering from structured and time-series enterprise data, and model evaluation and monitoring
• Working knowledge of core enterprise data domains such as finance, supply chain and master data
• Systems thinking and the ability to turn business rules into data and ML solutions across platforms

Nice to have

• Hands-on experience with a cloud data platform such as Snowflake or Databricks
• Distributed processing with Spark / PySpark, DuckDB or similar

Before you apply

• This role is not for people who prefer clean, well-documented datasets inside a single platform team, or who would rather hand a pipeline or model over than own it through client sign-off

About the company

Tessera Labs is an AI-native platform for enterprise transformation, with a multi-agent platform that delivers governed execution across ERP, CRM, HCM and finance systems. It works across SAP, Oracle, Salesforce, Workday and other systems of record.