Data Forward Deployed Engineer (Applied Data & ML Engineering)

Location: Remote in the U.S.

Salary: $180K–$233K

Company

hirify.global is an AI-native software platform company that provides governed, multi-agent execution across enterprise ERP, CRM, HCM, and finance systems.

What you will do

• Embed with enterprise client teams to scope data and ML problems, map source systems, and deliver working outcomes.
• Own validation, reconciliation to source, delivery quality, and stakeholder sign-off.
• Design scalable ETL/ELT pipelines with SQL, Python, and dbt for ERP, CRM, HCM, and finance data.
• Build canonical enterprise data models and cross-system mapping rules for master and transactional data.
• Engineer features, build ML models for use cases such as forecasting and anomaly detection, and deploy and monitor them in production.
• Convert repeated client patterns into reusable Tessera platform components.

Requirements

• 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, including knowledge of finance, supply chain, or master data processes.
• Client-facing, consulting, or forward-deployed experience, with the ability to work directly with engineers, functional consultants, and business stakeholders.
• 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, plus dbt for transformation, testing, and documentation.
• Cloud platform experience with AWS, GCP, or Azure.
• At least one ML model built, deployed, and monitored in production on business data; experience with feature engineering from structured and time-series data, model evaluation, and monitoring.
• Systems thinking, strong analytical problem solving, evidence-based decision-making, and ownership of complex production-grade solutions that scale across enterprise environments.
• Comfort working with fragmented, duplicated, and cross-platform data and owning solutions through validation, reconciliation, and client sign-off.

Nice to have

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

Culture & Benefits

• Remote full-time role within the U.S.
• Work across several enterprise customers and landscapes with senior functional architects, Forward Deployed Engineers, and AI engineers.
• Reusable pipelines, canonical models, mapping rules, and ML components become part of the Tessera platform.
• Engineers own delivery decisions and customer adoption outcomes.
• Equal opportunity employer welcoming applicants from all backgrounds.