The Role
Own data correctness and reliability from telematics device and third-party API ingestion through the landing zone. Investigate data issues using SQL and Python, perform root-cause analysis, build automated validation and quality gates, establish observability and SLAs, define data contracts, and drive permanent fixes across engineering, platform, vendors, and firmware teams. The role also extends into ML and GenAI data validation, drift monitoring, and cross-product consistency.
Summary Generated by Built In
Company Overview
Questar Auto Technologies is an AI-powered fleet intelligence company transforming vehicle health management for commercial fleets. Drawing on 15+ years of connected vehicle data, our AI monitors hundreds of thousands of vehicles across four continents and predicts component failures weeks before they happen. We process tens of trillions of data points per year from our own in-vehicle devices and third-party telematics platforms.
Position Overview
We are seeking a hands-on Data Quality Engineering Lead to own the correctness and reliability of the data behind every the telematics indicators, KPIs, Health Scores and AI recommendations our customers act on, consistently across the entire Questar platform, including Fleet Health and Fleet Operations.
The immediate priority is the ingestion path: from the Questar telematics device and third-party telematics ingest APIs to the entry point of the GenAI pipeline (the “landing zone”), across streaming and static data. Direct ownership ends at the landing zone; beyond it, the role requires end-to-end understanding of how this data flows through to what users see in the Questar app, so upstream quality translates into accurate customer-facing outputs. The goal is to actively improve data correctness, not just monitor and report on it.
Key Responsibilities
Data Investigation, Root-Cause Analysis & Resolution
Qualifications
Education
What We Offer
If you are passionate about making data right, not just measuring it, we want to hear from you! Apply now and join us on our journey to redefine Fleet Health.
Questar Auto Technologies is an AI-powered fleet intelligence company transforming vehicle health management for commercial fleets. Drawing on 15+ years of connected vehicle data, our AI monitors hundreds of thousands of vehicles across four continents and predicts component failures weeks before they happen. We process tens of trillions of data points per year from our own in-vehicle devices and third-party telematics platforms.
Position Overview
We are seeking a hands-on Data Quality Engineering Lead to own the correctness and reliability of the data behind every the telematics indicators, KPIs, Health Scores and AI recommendations our customers act on, consistently across the entire Questar platform, including Fleet Health and Fleet Operations.
The immediate priority is the ingestion path: from the Questar telematics device and third-party telematics ingest APIs to the entry point of the GenAI pipeline (the “landing zone”), across streaming and static data. Direct ownership ends at the landing zone; beyond it, the role requires end-to-end understanding of how this data flows through to what users see in the Questar app, so upstream quality translates into accurate customer-facing outputs. The goal is to actively improve data correctness, not just monitor and report on it.
Key Responsibilities
Data Investigation, Root-Cause Analysis & Resolution
- Become the inside expert when it comes to the data flow from the initial ingest point to the “landing zone”, including the telematics device configuration, telematics device’s data transformation capabilities and limitations, back-end's data normalization, validation and enrichment flows.
- Understand not only what data is ingested and how, but why: the business logic behind each data element, what it is used for across the product, and the downstream impact of any change, connecting the dots across the solution.
- Investigate data issues hands-on with expert SQL and Python, down to the first bad record, when a vehicle stops reporting, a feed goes partial or two sources disagree.
- Apply a systematic root-cause method (device/firmware vs. ingestion vs. transformation vs. model) and own each issue end-to-end, from investigation through solution design, implementation and permanent resolution, using AI and Analytics tools (e.g., Claude code) to move faster.
- Build automated data validation suites in production and embed them as blocking gates in pipelines and CI/CD.
- Own freshness, latency, volume and anomaly monitoring per source and per fleet; run quality scorecards with SLAs and a data incident process.
- Define data quality requirements and acceptance criteria for new features, integrations and model releases before build starts; set data contracts with partners and device firmware owners.
- Drive permanent fixes through teams you don’t manage (R&D, platform, external partners, data vendors), and communicate data quality in business terms to leadership and customer-facing teams.
- Ensure data consistency across Questar app modules (Fleet Health and Fleet Operations)
- Over time, extend coverage into the ML and GenAI pipeline: model-input drift, stale data never shown as live, and no double-counting of overlapping signals.
- Define and own data quality KPIs: automated-check coverage to "the landing zone”, time to detect and resolve incidents, freshness SLA attainment, and customer-reported data issues.
Qualifications
Education
- Bachelor’s degree in Computer Science, Engineering, Data Science or a related field, or equivalent practical experience.
- 6+ years in data engineering, analytics engineering, data quality or data QA automation at Senior / Staff level;
- Production experience building automated data validation and quality gates, including validation at ingestion from devices and third-party APIs.
- High-volume time-series, IoT or event data experience, and a track record of root-cause analysis that led to permanent fixes.
- Advantage: telematics or vehicle data (J1939 / OBD-II), VIN data extraction, ML data validation, Data Privacy Rules (GDPR) and PII mapping and classification, and scale-up platform migrations.
- Expert SQL and strong Python; Big data / Spark / lakehouse / postgresql platforms.
- dbt tests, Soda or Deequ, and CI/CD for data; AI power-user with co-pilots and agents.
- Full stack: Embedded and Cloud environments.
- Strong ownership mindset and excellent communication with technical and non-technical audiences.
- Thrives in ambiguity; leads by doing, with potential to grow a small data quality function.
What We Offer
- A high-impact role where data quality directly shapes product trust and growth, in a fast-evolving, AI-driven fleet technology space.
If you are passionate about making data right, not just measuring it, we want to hear from you! Apply now and join us on our journey to redefine Fleet Health.
Skills Required
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience
- 6+ years of experience in data engineering, analytics engineering, data quality, or data QA automation at Senior or Staff level
- Production experience building automated data validation suites and quality gates, including ingestion validation from devices and third-party APIs
- Experience with high-volume time-series, IoT, or event data
- Track record of root-cause analysis leading to permanent data fixes
- Expert SQL skills
- Strong Python skills
- Experience with big data, Spark, lakehouse, or PostgreSQL platforms
- Experience with dbt tests, Soda, or Deequ
- Experience with CI/CD for data
- Ability to work across embedded and cloud environments
- Strong ownership mindset and excellent communication with technical and non-technical audiences
- Experience with telematics or vehicle data, including J1939 or OBD-II
- Experience with VIN data extraction
- Experience with ML data validation
- Experience with GDPR and PII mapping and classification
- Experience with scale-up platform migrations
- Experience using AI copilots and agents for data investigation and resolution
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The Company
What We Do
Questar Auto Technologies is a predictive vehicle health company introducing cutting-edge AI technology for automotive. Our technology consists of AI-based analytics software, advanced telematics, and years of accumulated data and intimate familiarity with automotive pain points. Questar uses unique prediction models that will provide accurate prognosis of future vehicle health events before they affect our customers – automakers, Tier 1 suppliers, and fleets, and help them unlock the value of vehicle data. These deep insights will change the way fleets are managed, optimize expenditure, increase operational efficiency and safety with a clear and aggressive ROI.
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