Description

We are seeking a Senior Data Engineer who is passionate about working with a data driven team along with building scalable and robust data pipelines with a track record of designing and implementing complex data architectures.
As a Senior Data Engineer specializing in PySpark, you will be responsible for designing, building, and maintaining large-scale distributed data processing systems. You will work closely with data scientists, data analysts, and other stakeholders to implement data solutions that meet their needs. Your primary focus will be on leveraging PySpark to develop and maintain high-performance, reliable, and scalable data pipelines that integrate with various data sources and data storage systems.
Key Responsibilities:
• Design and implement PySpark-based data processing pipelines that can handle large amounts of data and scale to meet future demands.
• Develop and maintain data ingestion and integration pipelines for various data sources and data storage systems utilizing GCP tools and resources.
• Work closely with product managers, data stewards, data analysts, and other stakeholders to understand their data requirements and design solutions that meet their needs.
• Collaborate with other team members to develop and maintain data quality and data governance processes, ensuring that data is accurate, complete, and up-to-date.
• Optimize data processing pipelines for performance, scalability, and reliability, using techniques such as parallel processing, caching, and compression.
• Monitor and troubleshoot data processing pipelines, proactively identifying and resolving issues to ensure data accuracy and availability.

Qualifications

• Bachelor's or master's degree in Computer Science, Information Systems, or a related field.
• At least 5 years of experience in data engineering, with a focus on PySpark and distributed data processing systems.
• Strong experience with PySpark, including Spark Core, Spark SQL, and Spark Streaming. • Experience with Apache Hadoop, HDFS, and related technologies.
• Experience with cloud-based data processing technologies, such as Amazon EMR, AWS Glue, or Google Cloud Dataproc.
• Experience with data warehousing and ETL tools, such as Apache Airflow, Apache NiFi, or GCP Data Pipeline.
• Strong programming skills in Python and proficiency with SQL.

Company Overview

Here at UKG, our purpose is people™. Our HR, payroll, and workforce management solutions help organizations unlock happier outcomes for all. And our U Krewers, who build those solutions and support our business, are talented, collaborative, and innovative problem-solvers. We strive to create a culture of belonging and an employee experience that empowers our people – both at work and at home. Our benefits show that we care about the whole you, from adoption and surrogacy assistance to tuition reimbursement and wellness programs. Our employee resource groups provide a welcoming place to land, learn, and connect with those who share your passions and interests. What are you waiting for? Learn more at www.ukg.com/careers  #WeAreUKG 

EEO Statement

Disability Accommodation

For individuals with disabilities that need additional assistance at any point in the application and interview process, please email UKGCareers@ukg.com.