ADAS Data & Analytics Engineer

Job title: ADAS Data & Analytics Engineer

Role Overview

We are looking for a Data & Analytics Engineer with 4–7 years of experience to work on ADAS validation, data processing, and analytics workflows. The role involves handling large-scale vehicle data, building automation pipelines, and generating insights to support decision-making.

Key Responsibilities

• Data Processing & Analysis

• Work with ADAS/event-based datasets from multiple sources (signals, logs, video-derived data)

• Perform data extraction, cleaning, and transformation using Python

• Analyze time-series data and derive meaningful insights for validation use cases

• Automation & Workflow Development

• Develop scripts and workflows for automated data processing and reporting

• Identify opportunities to automate repetitive analytics tasks using ML or rule-based logic

• Work with orchestration tools (Airflow/Flyte or similar) for pipeline execution

• Data Engineering & Cloud

• Handle large datasets (e.g., Parquet) and optimize data pipelines for performance

• Work with cloud platforms (preferably GCP/AWS) for data storage and processing

• Integrate APIs and databases for data access and processing

• Visualization & Reporting

• Build dashboards using Power BI / Tableau / similar tools

• Design KPIs and visualize insights for stakeholders

• Ensure clear and structured storytelling of data insights

• Collaboration & Domain Work

• Work closely with validation teams and SMEs to understand data requirements

• Support ADAS function analysis and validation workflows

• Contribute to continuous improvement of analytics use cases

• Required Skills

• Technical Skills

• Strong Python skills (Pandas, NumPy, data processing)

• Good SQL knowledge (RDBMS/NoSQL basics)

• Experience with large-scale data handling and processing

• Exposure to cloud environments (GCP/AWS preferred)

• Knowledge of dashboarding tools (Power BI/Grafana/Tableau)

• Good to Have

• Experience in ADAS / automotive domain

• Understanding of time-series data & signal processing

• Exposure to ML basics (classification, model usage)

• Knowledge of containerization (Docker/Kubernetes)

Qualifications

• Bachelor’s/Master’s in Computer Science, Electronics, or related field

• 4–7 years of relevant experience in Data Analytics / Data Engineering

• Behavioral Expectations

• Strong analytical and problem-solving skills

• Ability to work in a dynamic environment

• Good collaboration and communication skills

• Structured thinking and ownership mindset

Benefits

• Discounts for Employees Possible
• Health Benefits
• Mobile Phone for Employees Possible
• Meal-Discounts
• Company Retirement
• Hybrid Work Possible
• Mobility Offers
• Events for Employees
• Coaching
• Flextime Possible
• Parking
• Inhouse Doctor
• Good Public Transport
• Barrier-Free Workplace
• Near-Site Childcare
• Canteen, Café