AmazonPosted 3mo ago

Data Engineer II

Data Engineer II at Amazon scores 71 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

IN, KA, Bengalurumidfull-time

AI in this role

bedrocksagemaker

llm-integrationai-agents

FBA is seeking a Data Engineer to build AI-native data infrastructure that embeds intelligence as a foundational feature. If you enjoy innovating and want to contribute to an industry-changing business while building next-generation intelligent data platforms, this role is for you.

Core Responsibilities:

AI-Native Infrastructure & Real-Time Processing
- Engineer AI-native infrastructure supporting real-time data processing for AI/ML inference, training, and continuous learning
- Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access
- Develop infrastructure for agentic AI systems with multi-agent orchestration
- Implement GenAI-powered data quality, entity resolution, and metadata management

Data-as-a-Product Delivery
- Own end-to-end accountability for data products from ingestion to consumption
- Deliver data products with clear SLAs, quality metrics, and customer satisfaction measures
- Build self-service platforms with embedded governance, lineage, and discovery
- Establish data contracts and APIs for reliable, versioned data consumption

AWS Infrastructure & Pipeline Engineering
- Manage AWS resources: EC2, Lambda, S3, Redshift, Kinesis, EMR, SageMaker, Bedrock, Neptune
- Build high-quality pipelines supporting analysts, data scientists, and AI agents
- Implement CDC and event-driven architectures for real-time data availability
- Deploy infrastructure-as-code using CDK/Terraform

Required Qualifications
- 5+ years in data engineering with cloud-native architectures
- Strong AWS expertise (Redshift, S3, Glue, Kinesis, EMR)
- Proven experience with real-time streaming (Kafka, Kinesis, Flink)
- Hands-on AI/ML infrastructure experience (SageMaker, Bedrock)
- Proficiency in Python, SQL, and infrastructure-as-code

Preferred Qualifications
- Knowledge graphs (Neptune, Neo4j) and semantic layers
- GenAI applications and LLM integration patterns
- Vector databases and feature stores
- Data mesh and domain-oriented architecture

Build the foundational infrastructure powering next-generation AI-enabled data products at Amazon FBA.

Basic qualifications

- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines

Preferred qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Llm IntegrationAI AgentsBedrockSagemaker

Questions you could be asked

How have you integrated a large language model into a production application?
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?
Describe a typical day in a role like this one: which parts run through AI directly?

Adapt your resume

List these exact terms on your resume: Llm Integration, AI Agents, Bedrock, and Sagemaker. 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.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.