Data Analytics Engineer

3 - 5 years

11 - 15 Lacs

Posted:4 days ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

Role Overview

We are seeking a skilled Data Analyst with strong automotive analytics expertise to support our ADAS development, validation, and continuous improvement initiatives.

The role involves analyzing large-scale vehicle datasets, driver behaviour insights, sensor performance logs, and algorithm outputs to deliver actionable insights for engineering, calibration, and safety teams.

Key Responsibilities

  • Analyze ADAS sensor data (camera, radar, lidar, ultrasonic), vehicle dynamics, and ECU log data to identify patterns, anomalies, and performance trends.
  • Work with engineering teams to understand ADAS algorithm behaviour, KPI definitions, and performance metrics.
  • Support model validation by generating statistical reports, performance summaries, and scenario-based evaluations.
  • Build dashboards, data visualizations, and automated reporting pipelines for engineering and program teams.
  • Clean, preprocess, and transform large datasets using Python, SQL, or cloud-based tools.
  • Perform root-cause analysis of ADAS feature performance issuesfalse detections, missed detections, driver intervention events, etc.
  • Collaborate with software, systems, and calibration engineers to refine feature KPIs and data requirements.
  • Support scenario extraction, annotation reviews, and dataset quality checks.
  • Work on continuous improvement of ADAS performance across markets, driving conditions, and environmental factors.
  • Document findings, insights, and recommendations in clear technical reports.

Required Skills & Qualifications

  • Bachelors/Masters degree in Engineering, Computer Science, Automotive Engineering, Data Science, or equivalent.
  • Strong experience in Python, NumPy, Pandas, Matplotlib/Plotly, Jupyter.
  • Hands-on experience with SQL and cloud data platforms (AWS/GCP/Azure preferred).
  • Good understanding of ADAS functions such as: ACC, AEB, LDW/LKA, BSD, CTA, Park Assist, TJA, Highway Assist, etc.
  • Familiarity with CAN, LIN, automotive diagnostics, log formats (MDF, ROS bags, ARXML).
  • Exposure to vehicle dynamics, sensor fusion concepts, machine learning pipeline basics.
  • Experience with visualization tools such as Power BI / Tableau.
  • Strong analytical, problem-solving, and communication skills.

Preferred / Nice-to-Have Skills

  • Experience with sensor data tools (Vector CANape/CANalyzer, dSPACE, OxTS, Mobileye logs, etc.).
  • Understanding of ISO 26262, SOTIF, and automotive safety standards.
  • Familiarity with AI/ML applications in automotive.
  • Experience working with ADAS test vehicles, simulation tools, or proving grounds.
  • Soft Skills
  • Strong ownership mindset and ability to work in cross-functional teams.
  • Detail-oriented with a passion for data-driven engineering.
  • Ability to break down complex engineering problems into simple insights.

Qualifications

  • Bachelors/Masters degree in Engineering, Computer Science, Automotive Engineering, Data Science, or equivalent.

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