Senior Data Engineer & Data Scientist – Commercial Intelligence

International Motors, LLC offers a hybrid role in Lisle, IL focused on building commercial intelligence that turns complex enterprise data into practical, workflow-embedded insights. This position combines senior-level data engineering with machine learning and AI/LLM prototyping to support Retail Sales Management (RSM) capabilities and drive next-best-action and opportunity identification. Compensation is USD 160,000 - 240,000 per year, along with a comprehensive benefits package designed to support employee wellbeing.

What you’ll do

• Design, build, and maintain scalable data pipelines and data products that support RSM and broader commercial intelligence.
• Integrate and normalize customer, prospect, dealer, vehicle, sales, service, parts, and CRM/digital interaction data, along with external data, then develop modeling approaches that make it usable for intelligence and analytics.
• Create robust methods for identity resolution, entity matching, deduplication, normalization, data lineage, and data quality across complex commercial datasets.
• Build and operationalize analytical and machine-learning models for lead scoring, opportunity identification, customer segmentation, propensity, prioritization, and next-best-action recommendations.
• Embed intelligence directly into dealer and sales workflows, not just reports and dashboards.
• Partner with Product, Sales, Commercial, UX, Data, and Engineering teams to translate high-value business problems into scalable data and analytical solutions.
• Design reusable commercial data models, semantic structures, and ontology concepts for customers, prospects, vehicles, dealers, opportunities, and sales activity.
• Define and monitor data quality, model performance, and business-impact metrics, and resolve issues that affect trust in commercial intelligence.
• Prototype and evaluate AI/ML approaches, including generative AI and LLM-based capabilities, that improve decision-making and sales effectiveness.
• Establish engineering and data-science practices for testing, observability, documentation, governance, versioning, CI/CD, and production deployment.
• Own built solutions end-to-end, including operational readiness, production support, incident response, quality standards, and technical lifecycle management.
• Act as a senior technical leader on the RSM product team, influencing architecture and technical direction while mentoring other practitioners.
• Communicate complex analytical findings and technical decisions to technical teams, product leaders, commercial stakeholders, and senior leadership.

Qualifications

• Strong hands-on experience building production-grade data pipelines, data models, analytical products, and commercial intelligence at enterprise scale.
• Advanced SQL and Python with solid software-engineering practices.
• Experience with modern cloud data platforms and distributed processing; Palantir Foundry/AIP and/or Databricks are strongly preferred.
• Experience developing, deploying, and monitoring machine-learning or statistical models on large, complex datasets.
• Strong understanding of data quality, lineage, observability, governance, testing, and production operations.
• Experience solving entity resolution and identity matching, including customer-360, master-data, or similar commercial data challenges.
• Experience with commercial datasets including customer, sales, CRM, marketing, vehicle, transactional, service, parts, or related domains.
• Ability to translate ambiguous commercial problems into data products, models, experiments, and measurable outcomes.
• Experience embedding analytical intelligence into operational applications and workflows.
• Familiarity with LLMs, retrieval, AI agents, or AI-assisted decision systems.
• Demonstrated ability to influence technical direction and drive outcomes across Product, Engineering, Data, and business teams.
• Highly proactive, ownership-driven mindset with independence in ambiguity.
• Excellent written and verbal communication skills, including coaching and mentoring data scientists and data engineers.
• Education requirement: Master’s degree.
• Experience requirement: At least 5 years of data engineering, data quality and/or analytics, or statistical analysis experience (with additional experience ranges also listed).
• Lead experience: At least 2 years of lead experience.
• Legal authorization: Qualified candidates (excluding current employees) must be legally authorized on an unrestricted basis to work in the United States (US Citizen, Legal Permanent Resident, Refugee or Asylee). Sponsorship is not anticipated (e.g., H-1B).

Skills and technologies

• SQL, Python
• Palantir Foundry, AIP, OSDK, and ontology/ontology concepts
• Databricks and lakehouse/data-engineering patterns
• Machine learning, LLMs, generative AI, retrieval, and AI agents
• CI/CD, API-first and event-driven architectures
• Semantic modeling and ontology design
• API-first and event-driven architectures and integrating analytical data products into production applications

Compensation and location

• Location: Lisle, IL (hybrid)
• Salary: USD 160,000 - 240,000 per year

Benefits

• Competitive market-based compensation
• Comprehensive benefits package designed to support employee wellbeing