Forward Deployed Engineer (Alluvial)

About the Role

This role is part of the Alluvial Data & AI Platform organization, sitting at the intersection of engineering, analytics, and applied intelligence. You will be part of a global team that builds and deploys advanced data solutions across multiple markets, accelerating delivery through reusable platform capabilities.

Responsibilities

• Support the design, development, and deployment of analytical solutions using Microsoft Data & AI tools (Fabric, Synapse, Data Factory, Power BI, Azure ML).
• Develop and maintain ETL/ELT pipelines, notebooks, and APIs using Python, SQL, and PySpark.
• Build rapid prototypes that leverage Alluvial’s reusable components for data ingestion, semantic modeling, and visualization.
• Contribute to AI-assisted workflows (prompt engineering, Copilot integration, and low-code automation).
• Work with cross-disciplinary teams to understand client problems and translate them into deliverable solutions.
• Contribute to solution and system architecture, including component design, integrations, and data flows.
• Contribute to and progressively take ownership of software and analytical solution delivery from requirements gathering through deployment, maintenance, and iteration.
• Assist with deployment automation, CI/CD pipelines, and environment setup using GitHub Actions and Azure DevOps.
• Perform exploratory data analysis, statistical profiling, and model testing on structured and unstructured datasets.
• Participate in agile ceremonies and help document technical specifications and lessons learned for reuse.
• Collaborate with Alluvial platform engineers to identify opportunities for platform enrichment based on project feedback.

Requirements & Tech Stack

• Proficiency in Python and SQL for data transformation and analysis.
• Familiarity with the Microsoft Data & AI Stack—Azure Data Factory, Synapse, Fabric, Power BI, or Databricks.
• Understanding of data modeling, version control (Git), and agile delivery.
• Comfort with cross-functional collaboration across time zones and disciplines.
• Demonstrated curiosity, initiative, and self-motivation, with the ability to take ownership of work.
• Comfort working through ambiguity and unfamiliar situations to develop practical solutions.
• Seller-doer mindset, with an interest in client relationships and contributing to business development.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience).

Preferred Qualifications

• 3 years of experience building or delivering data, analytics, or software solutions.
• Experience or coursework in data science, machine learning, or applied AI.
• Familiarity with AWS and interoperability across cloud ecosystems.
• Exposure to Palantir Foundry or similar enterprise data platforms.
• Basic experience with DevOps CI/CD pipelines and containerized environments (Docker, GitHub Actions, or Azure Pipelines).
• Experience with Jupyter notebooks, pandas, and visualization libraries (Plotly, Matplotlib).
• Working knowledge of prompt engineering or LLM-assisted workflows.
• Experience with Databricks, including collaborative notebooks and data engineering workflows.
• Experience building reports and dashboards in Power BI, including data modeling and visualization.

Location

• Hybrid: 2 days per week at any US-based Jacobs office.