Senior Data Platform Engineer (Hadoop)
One of our Fortune500, a Global Insurance Client is looking for a talented Senior Data Platform Engineer to join the Data Management & Operations team. They have good flex-time, work-life balance and with opportunities to get bonus to up to four times per year!
If you have the right skillset, you are encouraged to apply for this role.
- Contribute to data platform designs, implementation, and operations with focus on end-to-end solutions and reusable frameworks/utilities.
- Install, upgrade, and manage Cloudera, Azure, and open-source Data Platforms, tools & tech stack
- Design and implement capacity, security model, access control, backup strategy, monitoring & alerting, service level of Data Platform
- Optimize and tune the Data Platform for performance improvemen
- Plan and execute platform upgrade, maintenance, backup tasks, and audit related tasks.
- Delivery of BI dashboards
- Work closely with data engineers, operation teams, and business teams
- Facilitate projects executions by providing clear information of platform design, architecture, infrastructure, capacity, operations, and proactively collaborations with project teams
【会社概要 | Company Details】
Global insurance company with over 40 years of experience in Japan with strengths in various sales channels and product lineup. The company focuses on creating diverse environments including but not limited to promoting the appointment of women.
【就業時間 | Working Hours】
9:00 - 18:00（Mon - Fri）(Work from home due to COVID)
【休日休暇 | Holidays】
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, Other Special Holidays
【待遇・福利厚生 | Services / Benefits】
各種社会保険完備（厚生年金保険、健康保険、労災保険、雇用保険）、 屋内原則禁煙（屋外に喫煙所あり）、 通勤交通費支給等
Social insurance, Transportation Fee, No smoking indoors allowed (Designated smoking area), etc.
- Excellent understanding of the architecture, products, design patterns, typical use cases of Big Data Platform.
- In depth knowledge and experience of Big Data Ecosystems, such as Hadoop, HDFS, Hive, Impala, Spark, Kafka, HBase, Phoenix, Solr.
- Experience in relevant Big Data technologies
- Experience with solution architecture, design, and implementation
- Hands-on experience with Linux, Windows server.