Telematics Data Engineer
Apply NowCompany: SysMind Tech
Location: Schaumburg, IL 60193
Description:
We are seeking a highly skilled and motivated Telematics Data Engineer to join our team. This role requires expertise in telematics, IoT, and commercial auto lines, coupled with strong analytical and coding abilities. The successful candidate will be responsible for designing, developing, and maintaining scalable data pipelines, analyzing telematics datasets, and providing thought leadership in leveraging telematics data for business outcomes. You will collaborate with cross-functional teams and work with data from aggregators and IoT sources to deliver actionable insights.
Key Responsibilities
Data Engineering & Development Data Analysis & Insights Thought Leadership IoT Integration & Data Aggregation Collaboration & Stakeholder Engagement
Qualifications & Skills
Education
Experience
Technical Skills
Analytical & Business Skills
Soft Skills
Preferred Qualifications
Key Responsibilities
- Build and maintain robust data pipelines for ingesting, processing, and storing telematics data from IoT devices and third-party aggregators.
- Develop efficient ETL processes to ensure high-quality data integration into analytics platforms.
- Write clean, reusable, and optimized code to handle large-scale datasets.
- Analyze telematics datasets to uncover patterns, trends, and actionable insights related to commercial auto lines, fleet performance, and driver behavior.
- Collaborate with data scientists to develop predictive models and risk assessment tools.
- Present insights to stakeholders through visualizations and reports using tools like Tableau or Power BI.
- Provide expertise on best practices in telematics data utilization for the commercial auto line industry.
- Stay ahead of emerging trends in IoT and telematics to recommend innovative solutions.
- Act as a subject matter expert in discussions on telematics data integration and application.
- Work with IoT devices and communication protocols to ingest real-time telematics data (e.g., GPS, accelerometers, fuel sensors).
- Integrate data from multiple sources, including third-party aggregators, into centralized platforms for seamless analysis.
- Evaluate data aggregator offerings to ensure accuracy, reliability, and alignment with business needs.
- Partner with underwriting, claims, and fleet management teams to address business challenges using telematics data.
- Collaborate with architects and analysts to align engineering solutions with organizational objectives.
- Support ad-hoc data requests and provide technical expertise to enhance decision-making.
Qualifications & Skills
Education
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
Experience
- 5+ years of experience in data engineering, with at least 2 years focused on telematics or IoT.
- Proven track record in the commercial auto line or fleet management domain is highly desirable.
Technical Skills
- Strong programming skills in Python, SQL, and Scala (or equivalent languages).
- Experience with data pipeline tools such as Apache Kafka, Apache Spark, or Airflow.
- Proficiency with cloud platforms (AWS, Azure, or GCP), including IoT-related services (e.g., AWS IoT Core, Azure IoT Hub).
- Knowledge of databases, including relational (e.g., PostgreSQL) and time-series databases (e.g., TimescaleDB).
- Familiarity with IoT protocols like MQTT, CAN bus, or CoAP.
Analytical & Business Skills
- Strong problem-solving and analytical skills for interpreting large datasets.
- Experience with visualization tools like Tableau or Power BI
- Understanding of data governance, security, and compliance standards in telematics.
Soft Skills
- Excellent communication and presentation skills for technical and non-technical stakeholders.
- Demonstrated ability to provide thought leadership and guide strategic decisions.
- Proactive, self-driven, and eager to learn new technologies and methodologies.
Preferred Qualifications
- Experience in machine learning or predictive modeling for telematics data.
- Understanding of insurance risk assessment and fleet management operations.
- Certification in cloud platforms (e.g., AWS Certified Data Analytics, Azure Data Engineer).