Amazon Data Engineer - Global Accounts Professional Services AWSI-SDT-APJ-Japan 

Japan 

461143523

people changes.Key job responsibilities
Solutions - Deliver on-site technical engagements with partners and customers. This includes participating in pre-sales on-site visits, understanding customer requirements, creating consulting proposals and creating packaged Big Data service offerings.Delivery - Engagements include short on-site projects proving the use of AWS services to support new distributed computing solutions that often span private cloud and public cloud services. Engagements will include migration of existing applications and development of new applications using AWS cloud services.A day in the life
About AWSDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- 5+ years of experience with data modeling, data warehousing, and building ETL pipelines
- Knowledge of AWS services including S3, Redshift, EMR, Kinesis and RDS.
- Experience with Open Source Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
- Ability to write code in Python, Ruby, Scala or other platform-related Big data technology
- Knowledge of professional software engineering practices & best practices for the full software development lifecycle, including coding standards, code reviews, source control management, build processes, testing, and operations

- Strong verbal and written communication skills with stakeholders (Japanese language preferred along with English as second language)
- Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets.
- Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc)
- Experience building data products incrementally and integrating and managing datasets from multiple sources
- Query performance tuning skills using Unix profiling tools and SQL
- Experience leading large-scale data warehousing and analytics projects, including using AWS technologies – Redshift, S3, EC2, Data-pipeline and other big data technologies
- Linux/UNIX including to process large data sets.
- 5+ years of leadership experience in a technical, customer-facing role in the technology industry
- Experience in working with data lakes, modern data architectures, Lambda type architectures
- Proficiency in writing and optimizing SQL
- Knowledge of AWS services including S3, Redshift, EMR, Kinesis and RDS.