Ring AI Data Management are seeking to hire a Data Engineer (a) to work in one of the largest and complex data warehouse (DW) environments, (b) to lead the design and implementation of the architecture of DW solutions for the Enterprise using multiple platforms, (c) to apply daily experience in the design, creation, management, and business use of large datasets.
Key job responsibilities
- Work with engineering and business stakeholders to understand data requirements
- Lead the design, model, and implementation of large, evolving, structured and unstructured datasets
- Evaluate and implement efficient distributed storage and query techniques
- Interact and integrate with internal and external teams and systems to extract, transform, and load data from a wide variety of sources
- Implement robust and maintainable code with clear and maintained documentation
- Implement test automation on code implemented through unit testing and integration testing
A day in the life
The successful candidate will be on the lookout for ways to optimise the information flow process,
stay on top of latest trends in data warehousing and be able to coordinate and work on multiple,
related projects.
About the team
The Ring AI Data Management team owns tools and services for Ring's growing ML-based R&D needs. The portfolio of services managed by the team comprises centralized R&D data ingestion, aggregation and building standardized data models for the performance management. We collaborate in teams dedicated to customer needs, and the services powering them. We lean towards bias for action and quick decision making.- Multiple years industry experience
- Proficiency in writing complex SQL with PostgreSQL, Redshift or other RDB
- Coding proficiency in at least one programming language: Python, Scala, Java
- Experience in data modelling, data warehousing and building ETL/ELT pipelines
- Experience with AWS, including Redshift, S3, RDS, Athena, Elastic MapReduce
- Data modelling experience and data warehouse technical architectures, reporting/analytic tools- Degree in Computer Science, Engineering, Mathematics, or a related field
- Data Warehousing experience with Redshift, Teradata.
- Experience with workflow management platforms for data engineering pipelines (ex. Apache Airflow)
- Experience with Big Data Technologies (Spark, Hadoop, Hive, Pig, etc.)
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
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