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Mid-level analytics engineer title, broad skillset required, and generalist data role increase applicant competition substantially.
Core data engineering skills transferable, but automotive recall/DMS domain experience raises industry specificity moderately.
Explicit minimum five years plus mandatory analytics, ETL, BI and integration skills makes shortlisting stringent.
Design, develop and maintain scalable analytics and BI solutions processing millions of automotive data points to identify trends, risks, and business opportunities.
Build and support data integrations, ETL/ELT pipelines, and APIs to ensure timely, accurate data flow between enterprise systems and Dealer Management Systems (DMS).
Leverage AI, automation, and advanced analytics to improve recall campaign effectiveness, dealer and operational performance, and automate reporting workflows.
Bachelor's degree in Computer Science, Data Analytics, Engineering, Mathematics, Statistics or related discipline.
Minimum 5 years of experience in analytics engineering, business intelligence, systems integration, data engineering, or advanced analytics.
Experience with large complex datasets, dashboard development (preferably Qlik Sense), and API integrations is implied.
Work Experience Required: Minimum five years explicitly mentioned.
Experienced in the automotive industry with knowledge of vehicle recalls, warranty operations, dealer operations, or aftersales business processes.
Familiar with Dealer Management Systems (DMS) and vehicle safety or emissions compliance programmes.
Skilled in applying AI, predictive analytics, machine learning, or natural language processing to business processes and reporting in an international, multi-cultural environment.