Job Title

BU / FUNCTION DESCRIPTION We are building a new AI Transformation center – which will integrate into parts of ADITRAC (Accelerated Digital Transformation Center) and becoming our strategic advisory and technology partner for solving complex challenges in the journey of achieving your digital objectives. We work with all the business functions within Transportation Solutions and Sensors BU to drive Digitalization and create AI-driven solutions.Our set-up is based on 3 main pillars to drive and deliver digitalization:Consulting and digital / AI advisory: Partner with each function to better understand challenges and design state-of-the-art solutions and agentsAI Solutioning and Technology center: Mastering all technical disciplines and solutions Project Management and Security: Ensuring delivery on time and budget and with the necessary security levels.ROLE OBJECTIVE AI performance is founded by data quality and data governance. This role ensures the team has the right data, with the right quality, with the right controls - so model outcomes are dependable and reliable. Own the end-to-end AI data lifecycle - from governed ingestion to training/evaluation datasets, data quality gates, lineage, reproducibility, and run-time monitoring - using AWS + Databricks as the production backbone. Guide and prepare the transformation of Sensors from Dashboard- to an AI-driven organization.RESPONSIBILITIES AI Data Strategy & Ownership (Operating Model)Translate AI use cases into data requirementsFeatures, labels, context documents, metadata, refresh cadence, retention rules.Define the “AI data products” needed for each solution (training set, evaluation set, inference inputs, reference corpora)Develop and maintain an AI data roadmap aligned to the data product roadmap – specific for Sensors BUDevelop a data-strategy to tranform from a data-dashboard oriented organization to an AI-first modelCollaborating with our DIA Dashboard organization (Philippine spoke team)Develop a data-strategy for our Sensors internal databases (e.g. SBI) Data Ingestion & Curation on AWS + Databricks Build and operate robust ingestion pipelines from enterprise sources into AWS + Databricks:Ensure data pipelines are:Incremental (cost-aware)Observed (metrics & logs)Reliable (SLAs for freshness and completeness)Establish BU-oriented AI Data Governance (Unity Catalog + AWS controls)Leverage Databricks Unity Catalog for table, column, and row-level controlsImplement classification & handling standardsPII/PCI/Confidential taggingRetention and deletion rules (e.g., right-to-delete)Audit trails and access logging-Define and maintain data contracts with source owners for schema, semantics, quality SLAs, and change processesData Quality Engineering (Hard Gates for AI Readiness)Define data quality dimensions and SLAs (AI-specific):Completeness, consistency, timeliness, uniquenessDistribution stability (for drift-sensitive features)Implement automated quality checks:Schema validation (breaking changes)Null/missingness thresholdsReferential integrityDistribution checks (mean/variance, quantiles, KL divergence where appropriate)Consider data quality dashboards & alerting:Pipeline failures and/or data freshness breachesQuality test failures (e.g. Block training or deployment when critical checks fail)Performance & Cost Optimization (AWS + Databricks economics)Optimize data storage and compute:Partitioning strategies and file sizingDelta optimization/compaction strategyCluster sizing, autoscaling, job schedulingEnsure cost transparencyProduction Operations & Support Readiness (Run Phase)Provide operational artifacts and support:Runbooks (pipeline recovery, backfills, reprocessing)On-call / escalation participation for data incidentsRoot cause analysis for quality issuesEnsure observability via SLAs/health checks for critical pipelinesEDUCATION/KNOWLEDGEBacholor degree: Computer Science, Software Engineering, Data Science, Artificial Intelligence / Machine Learning, Applied Mathematics or Engineering (with strong CS content)QUALIFICATIONS & EXPERIENCEData Engineering & Data Management AI / ML Data FoundationsData Quality Engineering Cloud & Platform FundamentalsPlatform-Specific Qualifications (Databricks + AWS)Certifications (Optional but highly valuable)DatabricksDatabricks Data Engineer ProfessionalDatabricks Machine Learning ProfessionalAWSAWS Certified Data Analytics – SpecialtyAWS Solutions Architect (Associate/Professional)5+ years of overall experienceMOTIVATIONAL/CULTURAL FITInnovation demeanor Problem solvingProactiveWorking in a fast paced and dynamic environmentPassion for technologySelf developmentResults drivenClear and concise communication both locally and globally