LinkedIn Hiring For Sr Data Engineer, LinkedIn Marketing Solutions at San Francisco, CA

$127,000 - $208,000/Yr

Unclassified - San Francisco, CA

Full-time - Mid Level

Remote - San Francisco, CA

5,001-10,000 employees

About the position

LinkedIn is seeking an experienced Data Engineer to enhance the efficiency and accuracy of data processing within the LinkedIn Marketing Solutions (LMS) team. This role focuses on developing and managing data pipelines, ensuring high data quality, and collaborating with cross-functional teams to optimize data operations. The Data Engineer will play a crucial role in advising data professionals and navigating complex data challenges, all while contributing to a collaborative and innovative work environment.

Responsibilities

• Design, develop, and manage data pipelines and workflows for efficient data processing using Trino SQL/Spark SQL and HDFS datasets.
• Perform code designs and reviews, approving test cases to ensure quality.
• Implement data quality checks and audits to maintain high data accuracy and integrity.
• Produce elegant, efficient designs and scalable code for future needs.
• Collaborate with cross-functional teams to understand data requirements and implement robust data solutions.
• Gather data requirements from domain experts and translate business needs into technical specifications.
• Act as a technical advisor and Subject Matter Expert for projects, providing process and design advice.
• Optimize data storage for performance and scalability, ensuring efficient ETL processes.
• Develop and maintain documentation related to data pipelines, QA, metrics, and data policy.
• Stay updated with industry best practices and emerging trends in data engineering and analytics.

Requirements

• Bachelor’s degree in engineering, computer science, data science, or a related technical field.
• 6+ years of experience in a data engineering or analytics engineering role.
• 2+ years of experience using SQL and optimizing SQL databases for performance (Trino SQL or Spark).
• Experience in managing data pipelines (like HDFS), data repository (like GitHub), workflows (like Apache Airflow), and ETL best practices.
• Ability to communicate complex technical concepts to both technical and non-technical individuals.
• Experience working with multiple stakeholders, setting project priorities, and delivering on Objectives and Key Results (OKRs).
• Experience automating script changes in Python.

Nice-to-haves

• Masters in engineering, computer science, or related technical field (such as statistics or data science).
• Excellent analytical skills in designing data workflows and analyzing data for anomalies.
• Familiarity with data governance principles.
• Program Manager experience.
• Demonstrated experience in managing data pipelines in HDFS.
• Experience running a scrum team and using Jira.

Benefits

• Annual performance bonus
• Stock options
• Comprehensive health insurance
• 401(k) retirement plan
• Flexible work hours
• Paid time off
• Tuition reimbursement
• Professional development opportunities