Senior Data & AI Engineer

Daimler Truck North America

. Build, prove out, and enable artificial intelligence, machine learning, and automation solutions across DTNA .

Posted 10/27/2026full-timeUnited StatesSenior💰 $117,000 - $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced proficiency in Python and SQL, with hands-on experience in building and deploying AI/ML and automation solutions. Capable of translating business objectives into production-ready solutions while fostering collaboration across teams and mentoring junior practitioners.

Highest-signal resume keywords

Python ProgrammingSQL ProficiencyAI/ML Solution DevelopmentCloud Data Platforms (Snowflake)DevOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical MethodsETL ProcessesAPI IntegrationCI/CD PipelinesAutomated TestingData ModelingLLMs and Agentic ApproachesProduction Code DevelopmentData Analytics

Soft Skills

CoachingCollaborationCommunicationMentoringProblem-Solving

Tools & Technologies

Conversational AI ToolsSelf-Service Analytics PlatformsAutomation ToolsBusiness Intelligence ToolsData Governance Tools

Certifications & Qualifications

Data Science CertificationMLOps Experience

Industry Keywords

Continuous ImprovementAutomotive IndustryTransportation IndustryManufacturing IndustryQuantitative Field

Tech Stack

Tools & technologies

CloudETLPythonSnowflakeSQL

About the role

Key responsibilities & impact

Build, prove out, and enable artificial intelligence, machine learning, and automation solutions across DTNA
Co-develop solutions with business teams so they can own, enhance, and sustain them
Translate business objectives into working solutions and rapid proofs of concept
Take prototypes to governed, production-ready solutions in partnership with IT, the Data Intelligence Hub, and business-embedded data teams
Apply continuous integration and delivery pipelines, automated testing, and documentation
Build reusable solution patterns connecting business data to conversational AI tools
Develop and share new ways of working with data, analytics, automation, and AI
Support Continuous Improvement colleagues in developing data, analytics, automation, and AI solutions
Serve as a technical reference for BDAT and across DTNA
Evaluate, pilot, and integrate self-service analytics, automation, and AI tools and platforms
Work with IT and platform teams on data connections, APIs, access, governance, usage and cost transparency, and auditing
Stay current on emerging data and AI trends, test them hands-on, and recommend adoption timing
Lead hands-on coaching and co-development engagements across business units
Provide technical consultation and innovative approaches to business challenges
Mentor and develop junior team members and data community practitioners
Collaborate with senior leadership, IT, the AI Center of Excellence, and the enterprise data community
Advise business units on appropriate AI/ML, automation, analytics, or BI approaches
Identify opportunities to apply data, analytics, and AI to strategic initiatives
Foster and grow a data and AI community through collaboration, knowledge sharing, and best practices
Participate in community events, workshops, hackathons, and the annual DT Week conference

Requirements

What you’ll need

Bachelor's degree and 5+ years of relevant experience, or 8 years of relevant experience in lieu of a degree
Advanced proficiency in Python and SQL
Ability to write, review, test, and productionize code, and sanity-check AI-generated output
Experience designing, building, and deploying AI/ML, automation, or data solutions beyond the prototype stage into production
Hands-on experience building with LLMs and agentic approaches
Strong grounding in machine learning and statistical methods
Hands-on experience with cloud data platforms such as Snowflake, including data modeling, ETL, and API integrations
Working knowledge of DevOps practices, version control, automated testing, and CI/CD pipelines
Ability to coach and co-develop with teams at all organizational levels
Ability to translate between business and technical audiences, including executives
Applicants must be legally authorized to work permanently in the country the position is located in at the time of application
Final candidate must successfully complete a criminal background check
Final candidate may be required to successfully complete a pre-employment drug screen
Exceptional candidates might have a degree in Business, Mathematics, Computer Science, Statistics, Analytics, or a related quantitative field
Exceptional candidates might have a master's degree in a quantitative field, Data Science certification or equivalent, MLOps experience, cloud governance/cost management experience, training and upskilling experience, BI and automation tool familiarity, engagement leadership experience, continuous improvement methodology familiarity, or manufacturing, automotive, or transportation industry experience

Benefits

Comp & perks

Annual bonus program
401k company contribution with company match up to 6%
Non-elective company contribution of 3–7% depending on age
Starting at 4 weeks paid vacation
13+ calendar holidays
8 weeks paid parental leave
Employee assistance program
Comprehensive healthcare plans
Wellness programs
Onsite fitness at some locations
Tuition assistance
Volunteer paid time off
Short-term and long-term disability plans