Forward Deployed Engineer – EU and US (East)

Outsized; Poland (ME); On-site; USD 200,880 - 267,840; Full time

Job summary

Outsized is seeking Forward Deployed AI/Data Engineers (Lead level) to support data-driven solutions for its initial customer base. The role will involve hands-on development across the analytics lifecycle while collaborating with customers to deliver PoCs and evolve the platform.

This is an urgent 4-month engagement, remote and aligned to EU or US East time zones, with limited travel and multiple positions available for immediate onboarding.

Qualifications

• 7+ years’ experience in data engineering or related field.
• Strong communication skills for customer-facing roles.
• Hands-on experience across full analytics lifecycle: modelling, pipelines, dashboards.

Responsibilities

• Lead the development of PoC data products for initial customers.
• Translate requirements into data models, pipelines, dashboards, and ML solutions.
• Work with customers to drive data mesh adoption across lifecycle from data integration to infrastructure.

Skills

Data engineering

Solution architecture

Power BI

AWS

Python

Data processing

Data modelling

PySpark

Prototyping

Tools

Looker

Power BI

Job description

Forward Deployed Engineer - EU and US (East)

Experience Senior (11-15 years) | Expert (15+ years)

Est. Start August 3, 2026

Duration 4 Months

Tech company in data management

Remote

United States

Poland

Spain

United Kingdom

Required Skills Data Engineering Solution Architecture Power BI AWS Python Data Processing Data Modelling PySpark Prototyping

Project Overview

A leading data platform organisation is seeking multiple Forward Deployed AI/Data Engineers (Lead level) to support the delivery of data-driven solutions for its initial customer base.

As part of the Field Engineering team, these consultants will work directly with customers to translate business requirements into Proof of Concept (PoC) data products built on the organisation’s operating system. The role will involve hands‑on development across the full lifecycle of analytics and data product delivery, while also contributing to the evolution of the platform through real‑world feedback.

This is an urgent requirement, with three positions available for immediate onboarding. Candidates must be highly self‑sufficient, requiring minimal ramp‑up time, and capable of operating in client‑facing environments.

The role is remote, aligned to EU or US East time zones, with limited travel expected aside from periodic company‑wide events.

Key Responsibilities

• Lead the development of PoC data products built on the organisation’s OS for initial customers
• Translate business requirements into data models, pipelines, dashboards, and machine learning solutions
• Work closely with customers to support adoption of data mesh across the full lifecycle, from data integration to infrastructure optimisation
• Design and build end-to-end data solutions, including prototyping and production deployment
• Manage the full lifecycle of PoC delivery, from ideation through to successful deployment
• Develop and test data using synthetic datasets before production release
• Collaborate with internal teams to provide feedback and improve platform capabilities and tooling
• Support continuous integration and deployment processes to optimise build and release cycles
• Engage directly with stakeholders, articulating solutions and demonstrating value

Your Background

• 7+ years’ experience as a Data Engineer, Forward Deployed Engineer, Field Solutions Engineer, or Solutions Architect
• Proven experience in customer‑facing roles with strong communication skills
• Hands‑on experience across the full analytics lifecycle, including data modelling, pipeline development, and dashboarding
• Experience with tools such as Looker, PowerBI or similar for demonstration purposes
• Strong programming capability in Python and/or other languages, with a focus on rapid prototyping
• Experience building and managing data processing pipelines using tools such as Airflow, Dagster, Prefect, or dbt
• Familiarity with machine learning environments such as PySpark and Pandas
• Experience working with cloud infrastructure, including Kubernetes, Google Cloud, AWS, or Azure
• Experience working with complex data pipelines in large‑scale data environments
• Strong interest in applying data to machine learning and analytics use cases

Desirable:

• Understanding of data mesh principles
• Experience contributing to open‑source or internal data infrastructure products
• Experience solving ambiguous business problems with end‑to‑end data solutions
• Ability to quantify and communicate the business value of data solutions
• Experience with test‑first data pipeline development