Data Engineer II, Compliance Shared Services, RISC

Amazon is hiring a Data Engineer II, Compliance Shared Services, RISC in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this data engineer role is Uses AI ●●○○: an ordinary role that requires AI tools.
The posting mentions Bedrock, Python and Spark among its tools and skills.
Level classes it as a mid-level role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design and maintain robust data pipelines, data warehouses, and GenAI-powered automation tools for compliance.

BedrockPythonSparkSQLAWSRedshiftS3GlueLambda

ai-agentsetldata-engineeringdata-warehousinggenai

Amazon Regulatory Intelligence Safety and Risk (RISC) team mission is to protect customers from products that are unsafe, illegal, illegally marketed, controversial or otherwise in violation of Amazon's policies while enabling our Selling Partners to offer their broadest selection of safe and compliant products. We achieve these objectives worldwide by: (1) taking a science-first approach to offer trustworthy listings to our customers, (2) inventing intuitive and precise tools to simplify our selling partners' compliance journey and (3) innovating to reduce our cost to serve. The RISC Data Engineering team is seeking an experienced Data Engineer to join our team. In this role, you will be responsible for designing, building, and maintaining large scale robust data pipelines and infrastructure to empower our data and analytics initiatives. You will collaborate closely with tech teams and business stakeholders to understand their requirements and support with scalable data solutions. Join our expert team to build scalable data solutions, improving Amazon business efficiency and simplifying our selling partners' compliance journey.

Key job responsibilities
1. Design, develop, and maintain automated ETL/ELT pipelines with monitoring using Python, Spark, SQL, and AWS services such as Redshift, S3, Glue, Lambda

2. Optimize data warehouse and data lake architectures using best practices for DDL, physical and logical table design, data partitioning, compression, and parallelization

3. Implement and support reporting and analytics infrastructure for internal business customers

4. Develop optimized data models and transformations to ensure high-quality, well-structured data for business and analytics applications

5. Develop and maintain enterprise-scale data security solutions including data encryption, database user access controls, logging, and permissions management for data warehouse and data lake implementations

6. Maintain data warehouse and data lake metadata, data catalog, and comprehensive user documentation

7. Collaborate with internal business customers and technical teams to gather, document, and implement requirements for data publishing and consumption via data warehouse, data lake, and analytics solutions

8. Build self-service tooling and automation (including GenAI-powered agents) that removes recurring manual effort from the data engineering workflow and reduces turnaround time for common requests such as dataset provisioning, table subscriptions, and compliance validation

9. Design and operate compliance-critical data validation pipelines (e.g., multi-stage matching/verification funnels, referential integrity checks, dead-letter-queue handling) that convert raw or model-generated data into accurate, auditable, and regulator-ready outputs

10. Monitor and optimize cluster/compute resource utilization (e.g., workload management tiers, job scheduling, cost-aware compute architectures) to improve reliability and reduce infrastructure spend

11. Stay current with emerging technologies, tools, and trends (including AI advancements), evaluating and incorporating them into the existing data ecosystem for continuous improvement

A day in the life
You'll build and maintain data pipelines that feed compliance reporting across RISC, manage the infrastructure behind them (clusters, cost, reliability), and help teammates apply the right security and data-handling guardrails before anything reaches production. You'll also work on solutions that let the broader analytics team scale, including GenAI tooling that automates repetitive requests so BIEs and BAs spend less time on pipeline upkeep and more on analysis. Some days you're deep in Spark or SQL, others you're reviewing an agent design or advising a stakeholder on the right data pattern to use.

About the team
Who Are We
We are a team of engineers building scalable data solutions to improve Amazon business efficiency and simplify our selling partners' compliance journey. Our mission is to give every analyst and compliance program at Amazon fast, reliable access to trustworthy data, so they can protect customers and help selling partners stay compliant without waiting on manual pipeline work. We own the data foundation behind the compliance programs, and the people who use what we build range from BIEs and program managers to compliance and legal teams who depend on that data being accurate and on time. As a data engineer here, you'll work directly with those teams to understand what they need and build the pipelines and tools that get them there.

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 in the cloud.

Mentorship and 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.

Basic qualifications

- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines
- Familiarity with orchestration patterns such as event-driven architectures (EventBridge, Step Functions, Lambda) and workload/cost optimization techniques for compute infrastructure

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)
- Experience building or operating GenAI-based tooling or agentic workflows (e.g., using frameworks/platforms like AWS Bedrock, MCP-based agents) to automate engineering or operational tasks

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

Data Engineer II, Compliance Shared Services, RISC at Amazon rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● 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. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer II, Compliance Shared Services, RISC is an open job at Amazon.
Level rates this role AI Level 2 of 4: Uses AI.
The role is based in IN, KA, Bengaluru.
The job was posted on August 25, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsETLData EngineeringData WarehousingGenAIBedrockPythonSpark

Also common in data engineer jobs at this level

Azure Databricks Machine learning Java Snowflake Google Cloud

Pay

Typical data engineer job: $146k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where data warehousing was part of your work. What did you do?
Tell me about a project where genai was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, ETL, Data Engineering, Data Warehousing, and GenAI. 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.
Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.

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