Data Engineer – Mobilisights (Stellantis Data-as-a-Service)

About Mobilisights

 

Mobilisights, a business unit of Stellantis, is building the future of connected vehicle data and real-time mobility intelligence.

 

With millions of connected cars and devices generating high-volume sensor data, we are creating a Data-as-a-Service (DaaS) platform that powers innovative applications for consumers, enterprises, and mobility ecosystems worldwide.

 

We operate with the scale of one of the world’s largest automotive groups—Stellantis (Jeep, Fiat, Maserati, Peugeot, and more)—and the mindset of a startup. That means rapid innovation, cloud-native engineering, and real-time data at massive scale.

 

We are building the foundation of a smarter world powered by streaming, real-time, cloud-based data platforms.

 

Role Overview – Data Engineer (Streaming / Cloud / Big Data)

 

We are looking for a Senior Data Engineer with strong experience building and operating large-scale, cloud-native, real-time data streaming systems.

 

In this role, you will design and build the core data infrastructure that powers Mobilisights’ data products—handling massive, real-time vehicle and IoT data streams with a focus on scalability, reliability, and low latency.

 

This is a hands-on engineering role focused on data platforms, streaming pipelines, AWS cloud architecture, and production-grade data systems.

 

Key Responsibilities

 

Data Platform & Architecture

· Design and build a scalable, cloud-native data platform capable of ingesting, storing, processing, and streaming massive real-time datasets

· Architect systems that support high-volume sensor data ingestion and near real-time processing

· Enable fast and reliable development of data products and analytics services

 

Streaming Data Engineering

• Build and maintain real-time streaming data pipelines

• Implement data processing workflows using modern streaming technologies such as:

• Apache Kafka

• Apache Spark / PySpark

• Apache Flink

• AWS Kinesis

• Ensure low-latency, high-throughput data delivery for downstream applications

 

Cloud Engineering (AWS Focus)

• Develop and optimize AWS-based data architectures

• Work with services such as:

• AWS EMR

• AWS EKS

• AWS Lambda

• AWS MSK (Managed Kafka)

• Implement Infrastructure as Code (IaC) and automated deployment pipelines

• Support secure, scalable, and production-ready cloud infrastructure

 

Data Reliability & Operations

• Ensure data consistency, reliability, and fault tolerance across pipelines

• Build and maintain:

• Monitoring systems

• Logging frameworks

• Alerting and observability tools

• Implement data quality checks and data loss detection mechanisms

• Participate in on-call production support and incident troubleshooting

 

Engineering Excellence

• Contribute to operational best practices including:

• Restartability of pipelines

• Error handling strategies

• System resilience and recovery

• Work closely with cross-functional teams to deliver production-grade data system

Qualifications

Basic Qualifications:

• Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or related field

• A minimum of 8 years of experience in software engineering or data engineering roles

• Strong experience building and operating cloud-native, production-grade data streaming systems

• Hands-on experience with real-time data architectures emphasizing:

• Scalability

• Low latency

• High availability

• Data quality and privacy

• Required or strong experience with:

• Streaming & big data technologies: Kafka, Spark, Flink, Kinesis

• Cloud platforms: AWS (EMR, EKS, Lambda, MSK)

• Data processing frameworks: Spark / PySpark

• Data architecture concepts: data lakes / lakehouse (Databricks experience a plus)

• SQL and relational database fundamentals

• Infrastructure as Code (Terraform or similar preferred)

• CI/CD and deployment automation in cloud environments

Preferred Qualifications:

• Experience with Databricks Lakehouse Platform

• Programming experience in Scala, Java, or Python

• Experience building data observability, monitoring, and data quality frameworks

• Experience in high-scale IoT, automotive, or sensor-based data systems

 

Mindset & Soft Skills:

• Curiosity and passion for learning new technologies

• Strong bias toward action and problem solving

• Ability to operate in a fast-moving, startup-like environment within a large global organization

• Strong ownership mindset with ability to support production systems

 

High Level Edits:

• Reorganized into standard job posting structure (co overview, role overview, responsibilities, qualifications, technical skills, nice to have)

• Optimized for job search visibility

• Clarified the role into a more “real job description”

• Shifted from marketing heavy language to candidate relevant messaging

• Improved scan ability and readability

• Standardized technical expectations

• Aligned seniority and expectations (this is a senior data engineer role minimum of 8 years)

• Expanded keywords that ATS systems and recruiters filters for