Telematics Data Analytics Engineer (Remote)

Vernovis, Ltd.; Cincinnati (OH); Remote; USD 90,000 - 120,000; Full time

Job summary

Vernovis, Ltd. is seeking a Data Analytics Engineer who thrives at the intersection of data, analytics, and business.

You will turn telematics, GPS, and sensor data into actionable insights for internal teams and customers, building dashboards and data models while ensuring data quality and reliability. The role involves working with multiple data sources, collaborating with stakeholders, and supporting production data pipelines in a fast-paced environment.

Qualifications

• 2+ years of experience with SQL and Python to analyze, transform, and troubleshoot data.
• Experience handling large, complex datasets and high‑volume data environments.
• Experience building dashboards with Tableau, Power BI, or similar tools (Tableau preferred).
• Ability to translate stakeholder questions into metrics, data models, and dashboards.
• Experience investigating data quality issues and pipeline failures across data sources.

Responsibilities

• Design, build, and maintain Tableau dashboards and data visualizations converting telematics and insurance data into insights.
• Partner with stakeholders to define metrics and KPIs and translate questions into analytical solutions.
• Use SQL and Python to query, analyze, transform, and validate large datasets across multiple sources.
• Develop analytical data models for dashboards, reporting, and ad hoc analysis.
• Support a large-scale production telematics data pipeline, monitor data health, and troubleshoot issues.

Skills

SQL

Python

Tableau

Data modeling

Data pipelines

Data quality

Stakeholder communication

Snowflake

IoT

Telematics data

Tools

Snowflake

Power BI

Tableau

Job description

Vernovis, Ltd. is seeking a Data Analytics Engineer who thrives at the intersection of data, analytics, and business.

You will turn telematics, GPS, and sensor data into actionable insights for internal teams and customers, building dashboards and data models while ensuring data quality and reliability. The role involves working with multiple data sources, collaborating with stakeholders, and supporting production data pipelines in a fast-paced environment.