Data Forward Deployed Engineer – Applied Data & ML Engineering
Tessera Labs, Remote in the U.S.
The role
We are looking for a Forward Deployed Engineer (FDE) for our Applied Data & ML capability. You will work directly with enterprise clients to turn fragmented, multi-system enterprise data into trusted data products and production ML models.
You will collaborate closely with client teams, SMEs and Tessera product engineers to translate complex business logic into data pipelines, canonical data models and applied ML solutions, and you will feed proven patterns back into the Tessera platform.
The role requires strong experience in SQL, Python, data modeling and applied machine learning, combined with the judgment to own ambiguous client problems end to end. This is a mid- to senior-level role.
This role owns delivery quality on your engagements: validation, reconciliation to source and stakeholder sign-off.
What you will do
- DEPLOY WITH CLIENTS
- Embed with client teams to scope data and ML problems, map source systems 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.
- BUILD AND HARMONIZE ENTERPRISE DATA
- Design and develop scalable ETL/ELT pipelines using SQL, Python and dbt to ingest and transform data from enterprise platforms, including ERP, CRM, HCM and finance systems.
- Design canonical enterprise data models and cross-system mapping rules that standardize master and transactional data.
- Implement validation, reconciliation and monitoring to resolve duplicate, inconsistent and legacy data.
- APPLY MACHINE LEARNING
- Engineer features and build models on enterprise data for use cases such as forecasting and anomaly detection.
- Deploy models to production and monitor them.
What you need
- 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.