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Job DescriptionAs a Data Engineer, you will work with cross-functional stakeholders to understand operational use cases and deliver data solutions that support business decision-making.
You will be responsible for the development of data pipelines, ensuring their security, reliability, and efficiency, as well as the design and maintenance of scalable datasets for analytics and reporting. While your primary focus will be data engineering, you will also have opportunities to contribute to broader data projects, including work that extends into analytics, applications, or user-facing components.
Responsibilities
- * Design, develop, and maintain data pipelines and ingestion processes to integrate data from multiple enterprise systems
- Ensure the reliability, efficiency, and performance of data pipelines and platform components
- Develop and maintain well-structured datasets, including contributing to metadata management and semantic modelling to ensure data is clearly defined and aligned with business meaning
- Maintain data quality, lineage, and observability, ensuring datasets are trusted, traceable, and fit for use
- Manage changes to data structures and pipelines over time, including schema evolution, refactoring, and deprecation activities
- Apply data security, access control, and compliance standards, including data classification, permissions, and appropriate handling of sensitive data
- Collaborate with stakeholders (e.g. SMEs, analysts, business users) to understand requirements, support correct data usage, and contribute to data governance activities
- Support the usability and maintainability of data products through documentation, knowledge sharing, and resolution of day-to-day support queries
- Contribute to broader data initiatives or projects where required, including work that may extend beyond core data engineering responsibilities
Experience Requirements
- * Master’s degree in computer science, electronics/systems/software engineering, data science, or a related technical field
- 2-5 years of experience in data engineering, data platform development, or ETL/data pipeline development
- Strong experience in Python and SQL, with exposure to distributed processing frameworks (e.g. Spark)
- Proven experience developing data pipelines and ETL processes from disparate data sources
- Experience of working within a multinational organization with international, cross functional teams
- Experience working with relational and/or large-scale datasets in enterprise environments
- Experience working in Agile environments
- Strong problem-solving skills and ability to work independently and collaboratively
- Effective communication skills to engage with both technical and non-technical stakeholders, with spoken and written English language proficiency
- Competent to reach into data sources to create new data extraction interfaces
*Equal Opportunity Employer*Lear Corporation is committed to fair, merit‑based employment practices and equal opportunity.
We provide reasonable accommodations in accordance with applicable law. For assistance during the application process, contact your recruiter directly.
Applicants must submit their resume for consideration using our applicant tracking system. Due to the high volume of applications received, only candidates selected for interviews will be contacted. Candidates must be legally authorized to work in the country where the position is located. Unsolicited resumes from search firms, employment agencies, or similar, will not be paid a fee and will become the property of Lear Corporation.
