As a Data Engineer, the selected candidate will leverage business analysis, data management, and data engineering skills to develop sustainable data tools supporting Stellantis's Portfolio Planning and Manufacturing functions. This role will collaborate closely with data analysts and business intelligence developers within the Manufacturing team. Job responsibilities include but are not limited to:
Having deep expertise in the design, creation, management, and business use of large datasets, across a variety of data platforms
Assembling large, complex sets of data that meet non-functional and functional business requirements
Identifying, designing and implementing internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using AWS, Snowflake, and other SQL and NoSQL technologies.
Working with stakeholders to support their data infrastructure needs while assisting with data-related technical issues
Maintain high-quality ontology and metadata of data systems
Establish a strong relationship with the central BI/data engineering COE to ensure alignment in terms of leveraging corporate standard technologies, processes, and reusable data models
Ensure data security and develop traceable procedures for user access to data systems
Qualifications, Experience and Competency Requirements:
Education:
Bachelor's or Master's degree in Computer Science, or related IT-focused degree
Experience:
Essential:
Possess 5-8 years of IT experience
Expert-level skills in writing and optimizing SQL.
Experience with Big Data technologies such as Hadoop/Hive/Spark.
Self-motivator skilled in prioritizing and managing multiple tasks and projects
Minimum 3 years of experience in the area of data engineering or data architecture: concepts, approach, data lakes, data extraction, data transformation
Design, develop, and implement scalable and reliable data pipelines on AWS.
Build and maintain data lakes, warehouses, and ETL workflows using AWS services such as S3, Glue, Lambda, Step Functions, and Redshift.
Optimize data storage and retrieval processes for performance and cost efficiency.
Work with structured and unstructured data from multiple sources.
Collaborate with data analysts, data scientists, and business stakeholders to meet data processing requirements.
Develop and manage data security, governance, and compliance standards in AWS environments.
Monitor and troubleshoot data pipeline performance, ensuring minimal downtime and optimal efficiency.
Automate deployment and monitoring processes using AWS CDK and CloudFormation
Implement event-driven architectures using AWS EventBridge.
Work with AWS IoT Core and Greengrass for IoT and edge computing solutions.
Ensure security best practices by managing IAM roles, AWS Secrets Manager, and Cognito.
Deploy, monitor, and troubleshoot containerized workloads on AWS ECS and ECR.
Configure and optimize AWS CloudWatch logs, metrics, and alarms for monitoring.
Use AWS DMS for data migration services.
Desirable:
Familiarity with data analytics, Engineering processes and technologies
Ability to work successfully within a global and cross-functional team
A passion for technology. We are looking for someone who is keen to leverage their existing skills while trying new approaches and share that knowledge with others to help grow the data and analytics teams at Stellantis to their full potential!
Specific Skill Requirement :
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