JOB TITLE: Data Software Engineer
LOCATION: Pleasanton, CA
DURATION: 4 months
PAY RANGE: $57-$67/hr
COMPANY:
Our client is a leading provider of enterprise cloud applications for finance and human resources.
About The Team
Data pipeline and ETL tooling are some of the most important components required to make Client successful. Unification of these tools enables us to simplify our development and invest all effort and enhancements into a single platform. Our Client tooling must enable Client applications to be easily built, maintained, deployed and validated. By platformizing our Client pipeline tools, *** can build many high value Client solutions very quickly. Today, Client productivity can play a huge role in product success - this investment into improving data pipeline and ETL tooling is exactly what our team does. We strive to provide industry-leading solutions to Client and data engineering problems for *** developers and *** customers. We are made up of an eclectic group of dedicated individuals who pull experience from almost every corner of *** and some of today's top tech companies. We take great pride in being relentlessly innovative, intensely encouraging, and persistently positive.
About the Role
- Transition Databricks pipelines to Data Engineering tooling on AWS
- Transition Databricks notebooks to AWS SageMaker Studio
- Develop features for Data Engineering tooling that promote data mesh architecture principles
- Lead teams through best practices in Client and Client Ops
- Influence the direction of our product vision and strategy with technical expertise and context
- Provide critical feedback for the team's technical designs, architecture, and decisions
About You
Basic Qualifications:
- 1 or more years of experience using Databricks
- 1 or more years of experience using Client pipeline tools: Airflow, Dagster, Client Flow, AWS Glue, Spark, etc.
- 2 or more years of experience using cloud compute technologies: AWS, GCP, etc.
- 3 or more years of experience building production grade software and practicing Agile methodologies
Other Qualifications:
- 2 or more years of experience building data mesh architectures
- 2 or more years of experience with Client ops
- 2 or more years of experience with machine learning and data science technologies
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