Foundry Data Engineer (Python, PySpark)

Lear, a global automotive technology leader in Seating and E-Systems, enables superior in-vehicle experiences for consumers around the world. Our diverse team of talented employees in 38 countries is driven by a commitment to innovation, operational excellence, and sustainability. Lear is Making every drive better™ by providing the technology for safer, smarter, and more comfortable journeys. Lear, headquartered in Southfield, Michigan, serves every major automaker in the world and ranks #186 on the Fortune 500. Further information about Lear is available at lear.com, or follow us on Twitter @LearCorporation.

Data engineers work closely with Subject Matter Experts (SMEs) to design the ontology (data model), develop data pipelines, and integrate Foundry with external systems containing the data. Data engineers also need to provide guidance and support on how to access and leverage the data foundation to create new workflows or analyze data.

Data Pipeline Development & Maintenance

-    Integrate new data sources to Foundry using Data Connection
-    Implement 2-way integrations between Foundry and external systems
-    Develop pipelines transforming tabular or unstructured data
-    Implement data transformations in Spark (Pyspark, Spark SQL) or Pipeline Builder (No-Code) to derive new datasets or create ontology objects
-    Set up support structures for pipelines running in production
-    Monitor and debug critical issues such as data staleness or data quality
-    Improve performance of data pipelines (latency, resource usage)
-    Design and implement an ontology based on business requirements and 
-    available data
-    Provide data engineering context for application development

Minimum Criteria Details

-    Between 1 and 3 years of experience, ideally in a customer-facing role
-    Experience in Python/PySpark, or experienced in another programming language and willing to learn Python and PySpark on their own
-    Data engineering experience preferred over data science
-    Programming experience requiring collaborative software development.

Coding Skills

-    Python – complete language proficiency
-    SQL – proficiency in querying language (join types, filtering, aggregation) and data modeling (relationship types, constraints)
-    PySpark – basic familiarity (DataFrame operations, PySpark SQL functions) and differences with other DataFrame implementations (Pandas)

Frameworks & Conceptual Clarity

-    Distributed compute – conceptual knowledge of Hadoop and Spark (driver, executors, partitions)
-    Databases – general familiarity with common relational database models and proprietary instantiations, such as SAP, Salesforce etc.
-    Git – knowledge of version control / collaboration workflows and best practices
-    Iterative working – familiarity with agile and iterative working methodology and rapid user feedback gathering concepts
-    Data quality – best practices

We offer:

- Catering allowance
- Benefit on work anniversary in accordance with Collective agreement.
- Company canteen
- Development programs.
- Flexible working time
- Training program for new employees.
- Possibility of career grow.
- Sports and cultural activities.
- Vitamins package, fruit days every month, christmas presents.
- Cofee for employees.
- Financial consultations.

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