MTS 1, Data Engineer

PayPal•San Jose, CA

51d•Hybrid

About The Position

PayPal, Inc. seeks MTS 1, Data Engineer in San Jose, CA Job Duties: Participate and collaborate with Product Owners and Cross functional teams in organization to understand and implement the business solution that can scale. Act as an engineering lead to work with various engineers across the different time zones and build various engineering solutions in collaboration with engineering managers within the organization. Work closely with enterprise architecture teams to design the solution for various cross partners for PayPal with build sustainable lake house for various downstream users. Proactively anticipate the problems and issues to keep the various teams and management informed in a timely manner. Serves as lead engineer lead and produce quality deliverables to support all the functions of the product life cycle. Design, Develop, test and maintain architectures for data pipelines which assembles large, complex sets of data that meet non-functional and functional business requirements. Align architectures with business requirements. Engineering data-driven solutions for optimal extraction, transformation and loading of data from various data sources using AWS, GCP and SQL technologies. Ensure code quality and maintainability by evolving architecture and tech stack, refactoring, standards and improving build and test systems. Plan the execution of projects in an effective and efficient manner. Contribute to enterprise cloud data platform development using test driven development and agile methodologies to solve business problems using data driven solutions. Monitor and test newly implemented applications for reliability, security, and performance. Document findings and present to senior management with proposed solutions. Utilize the subject matter expertise in big data engineering to design, implement the data lake house and data marts which supports data availability, data scalability and performance. Partial telecommuting permitted from within a commutable distance.

Requirements

Master's degree, or foreign equivalent, in Computer Science, Engineering, or closely related quantitative discipline plus three (3) years of experience in the job offered or three (3) years of experience in the field of software engineering or program analysis or Bachelor's degree, or foreign equivalent, in Computer Science, Engineering or closely related quantitative discipline plus five (5) years of experience in the job offered or five (5) years of progressively responsible experience in the field of software engineering or program analysis.
Cloud Computing - Google Cloud Platform.
Programming languages - Python and Scala.
Apache Hadoop.
Apache Spark, Presto,Druid.
HDFS,HBase,Hive.
Google Bigquery,DataFlow,Kubernetes.
Databases -Oracle,DB2 and SQLServer.
Batch Scripting.
SQL/PLSQL.
Any suitable combination of education, training and experience is acceptable.
Must be legally authorized to work in the U.S. without sponsorship.

Responsibilities

Participate and collaborate with Product Owners and Cross functional teams in organization to understand and implement the business solution that can scale.
Act as an engineering lead to work with various engineers across the different time zones and build various engineering solutions in collaboration with engineering managers within the organization.
Work closely with enterprise architecture teams to design the solution for various cross partners for PayPal with build sustainable lake house for various downstream users.
Proactively anticipate the problems and issues to keep the various teams and management informed in a timely manner.
Serves as lead engineer lead and produce quality deliverables to support all the functions of the product life cycle.
Design, Develop, test and maintain architectures for data pipelines which assembles large, complex sets of data that meet non-functional and functional business requirements.
Align architectures with business requirements.
Engineering data-driven solutions for optimal extraction, transformation and loading of data from various data sources using AWS, GCP and SQL technologies.
Ensure code quality and maintainability by evolving architecture and tech stack, refactoring, standards and improving build and test systems.
Plan the execution of projects in an effective and efficient manner.
Contribute to enterprise cloud data platform development using test driven development and agile methodologies to solve business problems using data driven solutions.
Monitor and test newly implemented applications for reliability, security, and performance.
Document findings and present to senior management with proposed solutions.
Utilize the subject matter expertise in big data engineering to design, implement the data lake house and data marts which supports data availability, data scalability and performance.