Assignment Description

Our client in the automotive industry is currently seeking a Data Engineer with strong project management skills. You will be responsible for mapping an existing manual data collection process, designing and implementing a relevant data engineering and processing pipeline, and identifying and driving required components as one or several projects. This role requires a blend of technical expertise, project management skills, and a focus on data compliance and quality to ensure the successful delivery of data engineering solutions that meet business needs and regulatory requirements.

At our client’s Safety Centre, 200 highly skilled professionals strive every day to make the world a safer place for vehicle occupants, their loved ones, and the people around them. Covering the Safety and Durability attributes, they bravely lead the way for safety in alignment with the company’s strategic direction: Freedom to move in a Personal, Sustainable, and Safe way.

The Data, Analytics, and Artificial Intelligence team works primarily with real-world safety data to generate a deep understanding of crash and injury causation mechanisms. This knowledge forms the foundation for requirements on future safety features and functions in upcoming car development programs. It is provided to their car programs through data analysis and insights that support the engineering of world-leading products.

Overview of Responsibilities

Process Mapping & Analysis:

• Analyze and document existing manual data collection processes, workflows, and pain points.
• Identify opportunities for process optimization and automation within the data pipeline.

Pipeline Design & Implementation:

• Design a robust, scalable, and efficient data engineering and processing pipeline that meets the requirements of the mapped process.
• Select and implement appropriate tools, technologies, and frameworks for data ingestion, transformation, storage, and processing.
• Ensure data quality, integrity, and consistency throughout the pipeline.
• Implement data validation, error handling, and monitoring mechanisms to maintain high data quality standards.

Data Compliance & Governance:

• Ensure all data engineering practices comply with relevant data protection regulations (e.g., GDPR, CCPA) and internal data governance policies.
• Implement and enforce data access controls, encryption, and anonymization techniques where necessary.
• Collaborate with legal, compliance, and IT security teams to address any data-related compliance issues.

Project Identification & Management:

• Identify and prioritize necessary components and tasks required to transition from the manual process to an automated data pipeline.
• Develop detailed project plans, including scope, timelines, resource requirements, and risk assessments.
• Lead and manage data engineering projects, ensuring they are delivered on time, within scope, and to the required quality and compliance standards.
• Collaborate with cross-functional teams, including data analysts, data scientists, software engineers, and business stakeholders, to ensure alignment and successful project outcomes.

Data Quality Management:

• Establish and maintain data quality metrics and KPIs.
• Implement automated data quality checks and validation processes to detect and rectify data quality issues.
• Collaborate with data stewards and business users to define and enforce data quality standards across the organization.

Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; Master’s degree preferred.
• 5+ years of experience in data engineering, with a strong focus on data pipeline design, implementation, and optimization.
• Proficiency in programming languages such as Python.
• Experience with data processing frameworks (e.g., Apache Spark, Apache Kafka).
• Strong knowledge of database systems (SQL and NoSQL) and data warehousing solutions.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and related data services.
• Solid understanding of data governance, data privacy regulations, and compliance requirements.
• Proven experience in managing and delivering complex data engineering projects.
• Strong analytical, problem-solving, and communication skills.
• Familiarity with data quality tools and practices.

Desired Attributes:

• A passion for data engineering and analysis.
• A structured way of working and good documentation skills.
• A self-driven and result-oriented team player.
• Willingness to learn and improve.