
- Mitarbeiter
đ Automobilindustrie
đĄď¸ Versicherung
đź Beratung
Automotive ⢠Insurance ⢠Consulting
JDPA LIMITED ist ein Anbieter von Daten-, Analyse- und SoftwarelĂśsungen fĂźr das Automotive-Ăkosystem und angrenzende Finanz- und Versicherungssektoren. Das Unternehmen bietet Fahrzeugbewertungen, Markt- und Einzelhandelsinformationen, Qualitäts- und Kundenerfahrungs-Benchmarks sowie digitale Marketing- und Beratungsdienste fĂźr OEMs, Händler, Versicherer und Kreditgeber. JDPA LIMITED kombiniert proprietäre Kunden- und VIN-Daten mit fortschrittlichen Analysen und SaaS-Produkten, um Kunden dabei zu helfen, Produktdesign, Einzelhandelsleistung, Risikomanagement und Finanzoperationen zu verbessern.
đ vor 1 Monat
đ Kanada, Vereinigte Staaten â Remote
đľ $100.000 - $120.000 / Jahr
â° Vollzeit
đĄ Mittelstufe
đ Senior
đ§âđť Full-Stack-Entwickler
đť Geisterscore 5%
đŁď¸đşđ¸đŹđ§ Englisch erforderlich
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- Mitarbeiter
đ Automobilindustrie
đĄď¸ Versicherung
đź Beratung
Automotive ⢠Insurance ⢠Consulting
JDPA LIMITED ist ein Anbieter von Daten-, Analyse- und SoftwarelĂśsungen fĂźr das Automotive-Ăkosystem und angrenzende Finanz- und Versicherungssektoren. Das Unternehmen bietet Fahrzeugbewertungen, Markt- und Einzelhandelsinformationen, Qualitäts- und Kundenerfahrungs-Benchmarks sowie digitale Marketing- und Beratungsdienste fĂźr OEMs, Händler, Versicherer und Kreditgeber. JDPA LIMITED kombiniert proprietäre Kunden- und VIN-Daten mit fortschrittlichen Analysen und SaaS-Produkten, um Kunden dabei zu helfen, Produktdesign, Einzelhandelsleistung, Risikomanagement und Finanzoperationen zu verbessern.
⢠Work hands-on with quantitative data to create new capabilities and improve existing ones ⢠Develop data products solving critical problems for the auto industry ⢠Own end-to-end responsibility for business-critical projects ⢠Ensure technical excellence across the team ⢠Drive organizational capability through knowledge transfer and mentorship ⢠Immerse daily in automotive industry data, including complex business rules and data management ⢠Own the full development lifecycle: architecture, development, testing, and bug resolution ⢠Collaborate with stakeholders to define data requirements and translate business problems into technical solutions ⢠Engineer robust, extensible data pipelines using Snowflake, Dataproc, Airflow, Cloud Composer, and BigQuery ⢠Design, troubleshoot, and execute repeatable data processes ⢠Identify bottlenecks and optimize efficiency and reliability ⢠Analyze complex issues and communicate findings to business leadership ⢠Enforce engineering best practices and identify security vulnerabilities ⢠Mentor junior engineers on technologies, processes, and industry domain knowledge ⢠Lead cross-functional initiatives across Consulting, New Product Development, Data, and Engineering teams ⢠Serve as a strategic technical advisor for data-driven business solutions
⢠Bachelor's degree in Statistics, Mathematics, Econometrics, Operations Research, Quantitative Marketing, Finance, Engineering, or similar field ⢠6+ years of full-time quantitative analytics and data engineering experience ⢠Expert in SQL and Python ⢠Proficiency in modern cloud data platforms, including GCP BigQuery and Snowflake ⢠Highly skilled in ETL processes with demonstrated efficiency and accuracy outcomes ⢠Hands-on experience with Airflow, Cloud Composer, and Dataproc ⢠Experience integrating complex, multi-source datasets with multiple dimensions and layers of complexity ⢠Track record of resolving data quality issues creatively and effectively ⢠Ability to flag anomalies and inconsistencies using strong judgment ⢠Ability to translate technical analysis into clear business insights ⢠Effective written and verbal communication ⢠Subject matter expertise or ability to quickly develop deep domain knowledge in industry-specific business rules and processes ⢠Proficient with AI-assisted development tools such as Copilot, Cursor, or Claude Code ⢠Ability to judge when to accept, edit, or reject AI-generated output ⢠Skilled at providing effective context, including codebase conventions, requirements, and constraints ⢠Experience using AI to accelerate test authoring, documentation, and routine refactoring ⢠Awareness of AI tool limitations, including hallucinated APIs, outdated patterns, security pitfalls, and need for human verification ⢠Self-directed and detail-oriented, able to own work from requirements through release ⢠Strong communication and problem-solving skills ⢠Comfortable working across technical and business stakeholders ⢠Supports team growth through peer reviews, pairing, and mentorship
⢠Accommodation support during the recruitment and selection process ⢠Diverse and inclusive workplace commitment
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