Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Snr Data Engineer - Global Accounts, Professional Services, AWSI-SDT-APJ-Japan

Amazon
London
1 week ago
Create job alert

Snr Data Engineer - Global Accounts, Professional Services, AWSI-SDT-APJ-Japan

Job ID: 2923468 | Amazon Web Services Japan GK

AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.

Our AWS Professional Services consultants deliver IT infrastructure and application architecture guidance, lead proof-of-concept projects, perform enterprise portfolio assessments, review operational best practices and conduct skills transfer workshops. AWS consultants collaborate with customers and partners to address security and compliance, performance and scale, availability and manageability. They advise customers on data platforms using the full range of AWS services. They also assist with the non-technical change management work on policies, processes and
people changes.

At AWS, we’re looking for technical architects to collaborate with our customers and partners on key engagements, while helping our partners to develop technical expertise and capacity. The individual requires a strong combination of technical experience, hands-on keyboard capacity, technical leadership experience, and ability to learn fast in a fast paced environment. They will focus on customer solutions that enables customers to be a data-first organization.


#aws-jp-proserv-ap
#AWSJapan

Key job responsibilities
Expertise - Collaborate with AWS field sales, pre-sales, training and support teams to help partners and customers learn and use AWS services such as Amazon Elastic Compute Cloud (EC2), S3, AWS Glue, DynamoDB NoSQL, Relational Database Service (RDS), Elastic Map Reduce (EMR) and Amazon Redshift.

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.

About the team
About AWS

Diverse 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.

Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

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
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

BASIC QUALIFICATIONS

- Bachelor's degree in Computer Science, Engineering, Math, or related discipline
- 7+ years of experience with data modeling, data warehousing, and building ETL pipelines
- 10+ 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.
- 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)

PREFERRED QUALIFICATIONS

- 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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.