Senior Data Engineer

Role Overview: As a Data Engineer at Lear, you will play a crucial role in ensuring the seamless integration of data and analytics within the Foundry platform. Your responsibilities will revolve around building and maintaining robust data pipelines, producing high-quality datasets, and supporting the organizations data-driven decision-making processes. If you thrive in a dynamic environment and have a passion for data engineering, this role is for you. Key Responsibilities: - Manage Execution of Data-Focused Projects: - Oversee data-focused projects using Lears data analytics and application platform. - Participate in projects from conception to root cause analytics and solution deployment. - Understand program and product delivery phases, contributing expert analysis across the lifecycle. - Author data pipelines using a visual interface. - Manage code for data pipeline development. - Data Lineage: - Visualize end-to-end data. - Work with both new and legacy technologies to integrate separate data feeds and transform them into new scalable data. - Data Pipeline Development: - Collaborate with cross-functional teams to design, build, and maintain data pipelines. - Ensure data pipelines are efficient, reliable, and scalable. - Implement best practices for data ingestion, transformation, and enrichment. - Big Data, Dataset Creation and Maintenance: - Utilize pipeline or Code repository to transform big data into manageable datasets. - Produce high-quality datasets that meet the organizations needs. - Work closely with data scientists, analysts, and operational teams. - Provide transparency into data pipeline computation and handling. - Compliance and Data Security: - Ensure compliance with data regulations and implement data security measures. - Quality Assurance & Optimization: - Optimize data pipelines and their impact on resource utilization of downstream processes. - Continuously test and improve data pipeline performance and reliability. - Optimize system performance for all deployed resources. Qualifications Required: - Bachelors degree in Computer Science, Engineering, or a related field. - Proven experience in data engineering, ETL (Extract, Transform, Load), and data integration with Palantir Foundry (At least 2 years). - Familiarity with big data technologies. - Proficiency in programming languages such as Python, Java, and Typescript. - Proficiency in Python libraries for big data like PySpark, pandas, and Numpy. Role Overview: As a Data Engineer at Lear, you will play a crucial role in ensuring the seamless integration of data and analytics within the Foundry platform. Your responsibilities will revolve around building and maintaining robust data pipelines, producing high-quality datasets, and supporting the organizations data-driven decision-making processes. If you thrive in a dynamic environment and have a passion for data engineering, this role is for you. Key Responsibilities: - Manage Execution of Data-Focused Projects: - Oversee data-focused projects using Lears data analytics and application platform. - Participate in projects from conception to root cause analytics and solution deployment. - Understand program and product delivery phases, contributing expert analysis across the lifecycle. - Author data pipelines using a visual interface. - Manage code for data pipeline development. - Data Lineage: - Visualize end-to-end data. - Work with both new and legacy technologies to integrate separate data feeds and transform them into new scalable data. - Data Pipeline Development: - Collaborate with cross-functional teams to design, build, and maintain data pipelines. - Ensure data pipelines are efficient, reliable, and scalable. - Implement best practices for data ingestion, transformation, and enrichment. - Big Data, Dataset Creation and Maintenance: - Utilize pipeline or Code repository to transform big data into manageable datasets. - Produce high-quality datasets that meet the organizations needs. - Work closely with data scientists, analysts, and operational teams. - Provide transparency into data pipeline computation and handling. - Compliance and Data Security: - Ensure compliance with data regulations and implement data security measures. - Quality Assurance & Optimization: - Optimize data pipelines and their impact on resource utilization of downstream processes. - Continuously test and improve data pipeline performance and reliability. - Optimize system performance for all deployed resources. Qualifications Required: - Bachelors degree in Computer Science, Engineering, or a related field. - Proven experience in data engineering, ETL (Extract, Transform, Load), and data integration with Palantir Foundry (At least 2 years). - Familiarity with big data technologies. - Proficiency in programming languages such as Python, Java, and Typescript. - Proficiency in Python libraries for big data like PySp