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THE CHALLENGE Design, build, and implement generalized large-scale, sophisticated data pipelines using Nifi for downstream analytics and data science for our Sport Performance products. Design and develop scalable Nifi ingestion pipelines within AWS cloud services to consume real-time and batch data from external sources. Ensure the seamless integration of AWS-based tools for data storage, processing, and analytics. Responsible for ETL development and warehousing using Python and Java. Create data pipeline triggers and filters within ETL (extract, transform, and load) process to ensure appropriate optimization of data flowing through system and resource usage. Implement monitoring and error handling for all new parts of the data pipeline to ensure observability and alerting is available. Establish rigorous unit testing across the data pipeline to ensure robustness of the system. Design and create data models for use throughout the ETL system. Utilize Kafka to efficiently and to effectively store data to move throughout the data pipeline and for downstream data science and analytics usage. Design data architecture and data models for both internal and external representations of data. Build the data transforms within the data pipeline to convert data from external to internal representations. Conduct data analytics and debugging of bad data by writing SQL queries. Build automated cleaning of data to remove bad or unusable data from downstream consumers with logging to understand the frequency and depth of the underlying issues. Collaborate with other engineering teams to adopt standard methodologies, drive scalability, and increase consistency across systems. Maintain awareness of company standards and technology guidance; use JIRA, an Agile project mgmt. tool, to ensure efficient data development; collaborate with peers to align projects with overall direction. Follow best practices across Data Engineering to ensure scalable, consistent data architecture and system. Utilize Java language to build data processor in Nifi framework. Utilize Docker to ensure consistent, repeatable, and isolated environment for software development and testing. Work in a self-driven, independent fashion to meet Sport driven deadlines.
Job Responsibility
Design, build, and implement generalized large-scale, sophisticated data pipelines using Nifi for downstream analytics and data science for our Sport Performance products
Design and develop scalable Nifi ingestion pipelines within AWS cloud services to consume real-time and batch data from external sources
Ensure the seamless integration of AWS-based tools for data storage, processing, and analytics
Responsible for ETL development and warehousing using Python and Java
Create data pipeline triggers and filters within ETL process to ensure appropriate optimization of data flowing through system and resource usage
Implement monitoring and error handling for all new parts of the data pipeline to ensure observability and alerting is available
Establish rigorous unit testing across the data pipeline to ensure robustness of the system
Design and create data models for use throughout the ETL system
Utilize Kafka to efficiently and to effectively store data to move throughout the data pipeline and for downstream data science and analytics usage
Design data architecture and data models for both internal and external representations of data
Build the data transforms within the data pipeline to convert data from external to internal representations
Conduct data analytics and debugging of bad data by writing SQL queries
Build automated cleaning of data to remove bad or unusable data from downstream consumers with logging to understand the frequency and depth of the underlying issues
Collaborate with other engineering teams to adopt standard methodologies, drive scalability, and increase consistency across systems
Maintain awareness of company standards and technology guidance
Use JIRA, an Agile project mgmt. tool, to ensure efficient data development
Collaborate with peers to align projects with overall direction
Follow best practices across Data Engineering to ensure scalable, consistent data architecture and system
Utilize Java language to build data processor in Nifi framework
Utilize Docker to ensure consistent, repeatable, and isolated environment for software development and testing
Work in a self-driven, independent fashion to meet Sport driven deadlines
Requirements
Master's degree in Computer Science, Computer Engineering, or closely related field and 1 year experience as a data engineer or related occupation
1 year of experience with Python, Java, Kafka, AWS, and Docker
1 year of experience with ETL Development and Warehousing
1 year of experience with Analytic and debugging using SQL
1 year of experience with Agile development environment
1 year of experience with Designing data architecture
What we offer
A collaborative environment with colleagues from all over the world (Offices in Europe, Asia and US) including various social events and teambuilding
Flexibility to manage your workday and tasks with autonomy
A balance of structure and autonomy to tackle your daily tasks
Vibrant and inclusive community, including Women in Tech and Pride groups which welcome all participants
Global Employee Assistance Programme
Calm and Reulay app (leading well-being apps designed to support focus, quality rest, mindfulness, and long-term mental resilience)