Senior Data Engineer:

Women Back to Work, the prominent national organization specializing in return-ship programs, is pleased to collaborate with one of the leading companies in the retail industry, to extend return-to-work opportunities. The WBW Returnship program is exclusively designed for professionals who have taken a career break, whether for caregiving responsibilities, raising a child, or other voluntary reasons. If you have a gap in your work history, we warmly encourage you to apply. This Returnship provides a platform to enhance your skills, build on your experience, and cultivate meaningful connections. Join us in this empowering journey of professional resurgence. Primary Skills: Python (Expert), Spark (Advanced), SQL (Intermediate), ETL (Intermediate), AWS (Intermediate) Contract Type: W2 Location: Santa Clara, CA (Hybrid- 2 days in week) Duration: 6 months Contract #WBW Our client is seeking for a is seeking a Senior Data Engineer to enhance our SaaS product offerings by developing advanced data engineering solutions in Santa Clara, CA. You will have the opportunity to work closely with data scientists and product teams, driving innovation through data curation, platform development, and implementation of scalable data integration solutions. Key Responsibilities:

Curate and manage large-scale data collections for R&D purposes. Design and develop robust data storage solutions and APIs for data manipulation and retrieval. Implement monitoring mechanisms for data sources and maintain advanced analytics capabilities. Collaborate in design and deployment of applications, supporting data-centric development activities. Maintain tools for automation, deployment, monitoring, and continuous testing of data engineering processes.

Must-have skills

Proficiency in Python3 and experience with Spark. Strong background in SQL and ETL pipelines. Experience with AWS cloud services and data warehousing solutions like ClickHouse.

Industry Experience Required:

Extensive experience in data engineering and science, preferably within large-scale data environments across the networking or cybersecurity domain.

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