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AI Data Engineer Tokyo


06-05 AI Data Engineer/AIデータエンジニア


Professional Services & Consulting

8-12 million
 As a data engineer you will work in a dynamic and evolving environment following the strategic direction of Japan team. You are responsible for all aspects of helping clients with data architecture design, implementation, and optimization. You will develop, maintain and improve systems to meet particular needs, often as advised by systems architect. You will also do testing, test automation and bug fixing.
1. Responsible for teams to develop, maintain, test and evaluate data solutions within organizations. They possess deep industry and process knowledge to define problems, build solutions, and deliver end-to-end services that provide business insights to our customers utilizing data technologies. They have business acumen and domain
2. Knowledge with one or more of the following industries: finance, energy, healthcare, retail and banking.
3. Generally work on implementing complex data projects with a focus on collecting, parsing, managing, analyzing and visualizing large sets of data to turn information into. Insights using multiple skill sets these include code development and deployment, supporting data processing pipelines; data mining / science algorithms; and visualization engineering
4. Are the foremost experts in the lighthouse in data technologies, cloud / on premise / hybrid hosting solutions, and full-stack development.

1. Work in cross-disciplinary teams the industry experts to understand client needs and ingest rich data sources such as social media, news, internal / external documents, emails financial data, and operational data.
2. Rapidly architect, design, prototype, and implement architectures to tackle the Big Data and Data Science needs for a variety of large corporations and other major organizations.
3. Architect, implement and test data processing pipelines, and data mining / data science Algorithms on a variety of hosted settings, such as AWS, Azure, client technology stacks, and the company's own clusters.
4. Research, experiment, and utilize leading Big Data methodologies, such as Hadoop, Spark, Redshift, Netezza, SAP HANA, and Microsoft Azure.
5. Translate advanced business analytic problems into technical approaches that yield actionable recommendations, across multiple, diverse domains; communicate results and educate others through design and build of insightful visualizations, reports, and presentations .
6. Develop skills in business requirement capture and translation, hypothesis-driven consulting, work stream and project management, and client relationship development.
7. Strong experience with multiple large scale and / or distributed processing methodologies such as Hadoop, Storm, Spark, Etc. Experience with both cloud and on premise platforms.
8. Expertise to guide rapidly ingest, transform, engineer, and visualize data, both for ad hoc and product-level data & analytic solutions.
9.Expertise with programming methodologies such as version control, testing, QA, and development methodologies such as Waterfall and Agile.
10.Fluency or have previous coding experience in several programming languages such as Python, Clojure, Scala, or Java, with Java, with understanding of cloud and distributed systems principles, including load balancing, networks , scaling, in-memory vs. disk, etc .; and with large-scale, such as MapReduce, Hadoop, Spark, Hive, Impala, or Storm.
11.Ability to work efficiently under Unix / Linux environment or .NET, with experience with source code like systems like GIT.
12.Ability to work with team members and clients to assess needs, provide assistance, and resolve problems, using excellent problem-solving skills , verbal / written communication, and the ability to explain technical concepts to business audiences.
Language Skills
13.Business or higher level of English communication skills.
14.Japanese communication skills helpful but not necessary.