Senior Data Engineer, Selling Partner Agentic Interfaces Data Products
Technology, Data & Digital · Data, AI & Analytics · Data Engineering · Software Engineering · Business Intelligence
In short
Join SP-AI Data Products as a Senior Data Engineer to own the architecture of a data product that makes AI-powered commerce measurable and trustworthy for millions of sellers. You will define how the organization observes, governs, and learns from AI-driven interactions at scale, built on AWS infrastructure. This role involves designing and building streaming and batch ingestion pipelines, managing data architecture, and driving data engineering standards.
Responsibilities
- Own the design, implementation, and evolution of large-scale data architecture on AWS, ensuring production-grade reliability, scalability, and security.
- Write production-quality code in Java, Scala, and Python to build streaming and batch data pipelines processing terabytes of telemetry data daily.
- Design and maintain the canonical event schema and standardized, reusable data products following data mesh governance principles.
- Build and operate ETL and ELT pipelines using AWS-native services and JVM-based frameworks.
- Architect real-time observability infrastructure and analytical workloads.
- Collaborate with peer engineers, scientists, product managers, and BI engineers to define requirements and align data product design.
- Define and enforce data governance standards including schema governance, access control, data classification, naming conventions, and lineage tracking.
- Identify systemic data quality issues and architecture deficiencies, drive root-cause resolution, and automate manual processes.
- Document data products, architectural decisions, and design patterns clearly.
- Lead cross-team initiatives to enable GenAI capabilities through Amazon Quick Suite.
Requirements
- 7+ years of data engineering experience
- 5+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience
- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
- Experience with data modeling, warehousing and building ETL pipelines
- Experience leading engineering teams as a mentor or tech lead, or experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
Desired Qualifications
- Experience in any Bigdata architecture, or experience managing full application stacks from the OS up through custom applications and experience with automation and any version control tools
- Experience in Kafka, or experience in any Bigdata architecture and experience in Redshift
- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
Benefits
- Founding-team impact: You're defining the architecture an entire organization builds on, not inheriting legacy systems
- Breadth of influence: Your schema decisions, quality standards, and architectural patterns are consumed by risk teams, scientists, product managers, and leadership across the business
- Technical depth at scale: Streaming infrastructure, cross-surface correlation, schema governance for 50+ consumers, production SLAs on AWS. Hard, consequential engineering.
- Career-defining scope: Cross-cutting schema design and multi-team domain onboarding at this scale is the kind of work that shapes what comes next
#Data Engineering#AWS#AI#Machine Learning#Big Data#ETL#Streaming#Data Architecture#Schema Design#Data Governance
Company
Amazon
Job Posted
3 weeks ago
Employment Type
Full Time
WorkMode
On Site
Experience Level
Senior
Locations
Bengaluru, India
Applicants
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