Summary
✨ AI‑Generated
A lead data and analytics engineer is sought for a hands-on builder-lead role, spending most of the time on engineering and architecture while also mentoring and growing technical capabilities. The position involves shaping production data and AI systems for enterprise decision-making, with an initial focus on preparing complex customer datasets for optimization through conversational and agentic AI approaches.
Highlights
Builder-lead position combining substantial hands-on engineering and architecture work with technical leadership and mentoring. The role offers ownership of data and AI capabilities supporting enterprise decision-making and optimization use cases.
Description
Build the data backbone for AI-powered optimization.
This is a hands-on builder-lead role.
You will shape the architecture, write code, make important technical decisions, and help grow the engineering capability around you.
Approximately 70% of your time will be hands-on engineering and architecture, with the remaining time focused on technical leadership and mentoring.AIMMS is building the next generation of data and AI capabilities for enterprise decision-making in areas such as supply chain and energy.
We are looking for a Lead Data & Analytics Engineer to help turn this vision into production software.Your first mission: SENSAI Data ReadyYou will begin with product ownership for SENSAI Data Ready, an AI-native product that addresses one of the biggest bottlenecks in supply-chain analytics.Preparing large, imperfect customer datasets for optimization models can take weeks of manual work.
SENSAI enables supply-chain analysts to use conversational, agentic AI to inspect, join, validate, and transform multi-million-row datasets into reusable execution recipes—in minutes.From there, your scope will grow to defining and building the shared, persistent data backbone that enables future AIMMS applications.This is how you make a difference:Design and build scalable data products for large datasets Develop reliable AI-agent workflows for data inspection, transformation, and validationSolve challenging problems involving SQL generation, schema drift, joins, performance, and data qualityDefine the architecture and technical direction of the AIMMS Data BackboneBuild production-quality services, APIs, tests, and CI/CD pipelinesResearch, prototype, and evaluate new technologiesMentor engineers and raise the technical bar across the teamWork closely with Product, domain experts, and technical leadership
