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Employment: Unconfirmed

What you’ll work on

We are looking for a Data & Analytics Engineer with 4–7 years of experience to work on ADAS validation, data processing, and analytics workflows.

Work with ADAS/event-based datasets from multiple sources (signals, logs, video-derived data)
Develop scripts and workflows for automated data processing and reporting
Work with cloud platforms (preferably GCP/AWS) for data storage and processing

From the employer’s posting

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.

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

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

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

What you’ll bring

All qualifications

Core experience

Strong Python skills (Pandas, NumPy, data processing)
Experience in ADAS / automotive domain
Bachelor’s/Master’s in Computer Science, Electronics, or related field
Ability to work in a dynamic environment
Structured thinking and ownership mindset
Strong Python skills (Pandas, NumPy, data processing)

Qualification wording

Strong Python skills (Pandas, NumPy, data processing)

Experience in ADAS / automotive domain

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

Ability to work in a dynamic environment

Structured thinking and ownership mindset

Tools in this posting

Python
SQL
Tableau
NumPy
pandas
AWS
Google Cloud (GCP)
NoSQL
Power BI
Docker
Kubernetes
Grafana
Airflow

Source

- 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

Technical Skills - Strong Python skills (Pandas, NumPy, data processing) - Good SQL knowledge (RDBMS/NoSQL basics)

- Strong Python skills (Pandas, NumPy, data processing) - Good SQL knowledge (RDBMS/NoSQL basics) - Experience with large-scale data handling and processing

Visualization & Reporting - Build dashboards using Power BI / Tableau / similar tools - Design KPIs and visualize insights for stakeholders

- Exposure to cloud environments (GCP/AWS preferred) - Knowledge of dashboarding tools (Power BI/Grafana/Tableau) Good to Have

- 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

- Experience with large-scale data handling and processing - Exposure to cloud environments (GCP/AWS preferred) - Knowledge of dashboarding tools (Power BI/Grafana/Tableau)

- Exposure to ML basics (classification, model usage) - Knowledge of containerization (Docker/Kubernetes) Qualifications

- 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

Job description

View original posting ↗

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

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

Your next step

Have your CV and examples of relevant work ready.
Check the listed location, eligibility and core experience before starting.
Ask the employer about the salary range before committing time to the process.

Complete your application on jobs.mercedes-benz.com. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

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Pay

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Location & working pattern

Bengaluru, Indien

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Work authorization

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Open source at jobs.mercedes-benz.com ↗Read the full description ↓

Status in our records: Active
First seen by us: Jun 26, 2026
Recorded sightings: 168
Last seen by us: Oct 1, 2026

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