ADAS Data & Analytics Engineer
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Salary
≈ $16k – $39k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 4+ years exp
Confirmed on the employer's own hiring board on Oct 7, 2026. First seen by Alion on Sep 28, 2026.
Overview
Company
Impact
Profile match
Mercedes-Benz Group is a German carmaker whose lineage runs back to Karl Benz's patent motor car of 1886 and the 1926 merger of Daimler and Benz that created the modern company. It builds premium and luxury passenger cars and vans under the Mercedes-Benz, AMG, Maybach and G-Class brands, positioning itself deliberately at the high end of the market after separating its truck business into a standalone listed company in 2021. The group is rebuilding its vehicles around the MB.OS operating system and its own electric architectures, and it runs one of the most successful teams in Formula One as a technology showcase.
Aufgaben
Job Description - ADAS Data & Analytics Engineer (4-7 Years)
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
Qualifikationen
Job Description - ADAS Data & Analytics Engineer (4-7 Years)
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
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