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Snr Specialist Analytics SA – ASEAN, WWSO Data APJC
AI in this role
bedrocksagemakerdatabricks
ragai-agents
ASEAN is one of the fastest-growing data markets in the world, and many customers are still deciding where their data platform will live. You will work with banks, telcos, retailers, public sector agencies, and digital natives as they make that decision, often in head-to-head evaluations against Snowflake, Databricks, Azure Fabric, and GCP BigQuery. Grounded in deep analytics expertise, you will bring a broad perspective that spans databases, ML, and security, and you will advise on governance and access control as much as on performance and cost.
You will build reference architectures, demos, and workshops with your own hands and scale them across six countries through account teams and partners. Partners deliver much of the analytics work in ASEAN, so enabling them to land complex platforms such as SageMaker Unified Studio is a core part of the role. You will also carry the voice of ASEAN customers back to the AWS analytics, search, streaming, and generative AI service teams to shape their roadmaps.
Data is the context layer that turns generic AI into personalised, differentiated customer experiences. Every AI conversation is a data conversation, and this role sits at the centre of it for ASEAN. If you see that shift as an opportunity and want to co-create new value with customers across the region, come join us and build the future together!
Key job responsibilities
- Provide deep technical expertise in analytics, search, streaming, and governance (Redshift, Athena, EMR, Glue, Kinesis, MSK, OpenSearch, Lake Formation, DataZone, SageMaker Unified Studio, S3 Tables, QuickSight) across ASEAN's enterprise, public sector, and digital-native customers
- Design agent-ready data platforms on open lakehouse, Iceberg, zero-ETL, RAG, and semantic search
- Lead architecture reviews, immersion days, proofs of concept, and migrations (MAP) off Hadoop, legacy warehouses, and third-party platforms
- Win competitive evaluations against Snowflake, Databricks, Azure Fabric, and GCP BigQuery
- Enable partners and build repeatable assets that scale across six countries
- Carry customer feedback and competitive signals back to service teams to shape the roadmap
A day in the life
Your customers span Financial Services, Telecommunications, Retail, Public Sector, and Digital-Native companies. One morning you run an open data platform workshop in Singapore; by lunch you are designing governed data access for a Manila bank's first production agents. In the afternoon you build a RAG proof of concept with OpenSearch and Bedrock for a Jakarta retailer, then help a partner unblock a SageMaker Unified Studio rollout, before sending field feedback to the Redshift service team. You travel regularly across a region where the decisions customers make today will set their data platform for the next decade.
About the team
The WWSO Data & AI team helps customers adopt our newest and most advantageous technologies. This role sits on the APJC Data team alongside Analytics, Database, and Storage Specialist SAs and GTM Specialists across five geos. In ASEAN, you work closely with the Analytics GTM Specialist, the Database and Storage Specialist SAs, the partner team, and account teams in each country to deliver holistic data outcomes. If you thrive on going deep on technology, love building for customers, and measure success by the architectures you've shaped, this is the role for you.
Basic qualifications
- 7+ years of data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding experience
- Experience defining data center system-level architecture, documenting performance and equipment requirements, creating and communicating conceptual designs, and creating and maintaining project documentation
- Experience working with technical and business stakeholders from global cross-functional teams
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
- Deep hands-on experience with analytics technologies, including data warehousing (e.g. Redshift, Snowflake, BigQuery, Teradata), data lakes, ETL/ELT pipelines, streaming (Kafka, Kinesis, Flink), search (Elasticsearch/OpenSearch), and data governance.
Preferred qualifications
- Experience and demonstrated industry leadership in the fields of database or data warehousing, data sciences and big data processing
- AWS certification, such as, AWS Solutions Architect, or a similar cloud certification, or Bachelor's degree
- Experience designing agent-ready data platforms (open lakehouse, Iceberg, zero-ETL, RAG, semantic search)
- Experience across multiple Southeast Asian markets and building reusable assets at scale
- Fluency in English required; a Southeast Asian language (e.g. Bahasa Indonesia, Thai, Vietnamese) is a plus
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.
How we rate this
Snr Specialist Analytics SA – ASEAN, WWSO Data APJC at Amazon rates 77 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Classification
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
RAGAI agentsBedrockSagemakerDatabricks
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What are the limits of Bedrock that you've run into, and how did you work around them?
- What's a project where you used Sagemaker hands-on?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, Bedrock, Sagemaker, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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