Senior Data Engineer

2 weeks ago


PimpriChinchwad, India Lear Corporation Full time

Overview:

As a Senior Data Engineer at Lear, you will take a leadership role in designing, building, and maintaining robust data pipelines within the Foundry platform. Your expertise will drive the seamless integration of data and analytics, ensuring high-quality datasets and supporting critical decision-making processes. If you’re passionate about data engineering and have a track record of excellence, this role is for you

Responsibilities:

Manage Execution of Data-Focused Projects:

  • As a senior member of the LEAR foundry team, support in designing, building and maintaining data-focused projects using Lear’s data analytics and application platforms.
  • Participate in projects from conception to root cause analytics and solution deployment.
  • Understand program and product delivery phases, contributing expert analysis across the lifecycle.Ensure Project deliverables are met as per agreed timeline.

Tools and Technologies:

  • Utilize key tools within Palantir Foundry, including:
  • Pipeline Builder: Author data pipelines using a visual interface.
  • Code Repositories: Manage code for data pipeline development.
  • Data Lineage: Visualize end-to-end data flows.
  • Leverage programmatic health checks to ensure pipeline durability.
  • Work with both new and legacy technologies to integrate separate data feeds and transform them into new scalable datasets.
  • Mentor junior data engineers on best practices.

Data Pipeline Architecture and Development:

  • Lead the design and implementation of complex data pipelines.

Collaborate with cross-functional teams to ensure scalability, reliability, and efficiency andutilize Git concepts for version control and collaborative development.

  • Optimize data ingestion, transformation, and enrichment processes.

Big Data, Dataset Creation and Maintenance:

Utilize pipeline or code repository to transform big data into manageable datasets and produce high-quality datasets that meet the organization’s needs.

  • Implement optimum build time to ensure effective utilization of resource.

High-Quality Dataset Production:

  • Produce and maintain datasets that meet organizational needs.
  • Optimize the size and build scheduled of datasets to reflect the latest information.
  • Implement data quality health checks and validation.

Collaboration and Leadership:

  • Work closely with data scientists, analysts, and operational teams.
  • Provide technical guidance and foster a collaborative environment.
  • Champion transparency and effective decision-making.

Continuous Improvement:

  • Stay abreast of industry trends and emerging technologies.
  • Enhance pipeline performance, reliability, and maintainability.
  • Contribute to the evolution of Foundry’s data engineering capabilities.

Compliance and data security:

  • Ensure documentation and procedures align with internal practices (ITPM) and Sarbanes Oxley requirements, continuously improving them.

Team Development and Collaboration:

  • Mentor junior team members and contribute to their growth.
  • Foster collaboration within cross-functional teams.
  • Share best practices and encourage knowledge sharing.

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:

  • Bachelor’s or master’s degree in Computer Science, Engineering, or a related field.
  • Minimum 5 years of experience in data engineering, ETL, and data integration.
  • Proficiency in Python and libraries like Pyspark, Pandas, Numpy.
  • Strong understanding of Palantir Foundry and its capabilities.
  • Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).
  • Excellent problem-solving skills and attention to detail.
  • Effective communication and leadership abilities.


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