Senior Data Engineer, Selling Partner Agentic Interfaces Data Products

Hiring

Amazon

Bengaluru · IndiaFull-time· 2d ago

Experience

6+ years

Work Type

Full-time

Domain

AI-powered commerce, e-commerce

Leadership

Required

Core SkillsMust Have

AWSKinesisEMRApache SparkAWS GlueRedshiftAWS AthenaS3Lake FormationLambdaStep FunctionsJavaScalaPythonSQLKafkaETLELTdata governanceschema governancestreaming pipelinesbatch pipelinesfine-grained access controldata lineageQuickSightAmazon Quick Suitedata mesh

What You'll Do

1Design and govern the canonical event schema that makes every AI interaction produce a comparable, correlated record

2Own end-to-end data architecture across telemetry layers (user engagement, action execution, domain response) with cross-layer correlation through session-level tracing

3Build and operate streaming and batch ingestion pipelines on AWS with production SLAs serving real-time observability for leadership, risk teams, applied scientists, and product teams

4Architect tenantized data products enabling 50+ teams to onboard once and receive self-serve metrics (adoption, quality, risk, impact) without custom pipelines

5Drive data engineering standards across the organization: schema governance, naming conventions, data quality, operational excellence

6Make architectural trade-offs balancing short-term delivery against long-term scalability: tiered storage, build-vs-buy, schema evolution across dozens of consumers

7Identify and resolve systemic architecture deficiencies; propose and lead cross-team initiatives

8Decompose complex, ambiguous problems into parallel workstreams and reassemble them into cohesive solutions

9Elevate the engineering team through mentorship and technical leadership

10Own design, implementation, and evolution of large-scale data architecture on AWS providing system-wide technical guidance

11Write production-quality code in Java, Scala, and Python to build streaming and batch data pipelines processing terabytes of telemetry data daily

12Design and maintain canonical event schema and reusable data products following data mesh governance principles

13Build and operate ETL/ELT pipelines using AWS-native services and JVM-based frameworks (Spark on Scala/Java)

14Architect real-time observability infrastructure and analytical workloads (Kinesis, Redshift, Athena, QuickSight)

15Collaborate with and influence peer SDEs, Applied Scientists, Product Managers, and BI Engineers

16Define and enforce data governance standards including schema governance, Fine-Grained Access Control, data classification, naming conventions, and lineage tracking

17Identify systemic data quality issues, drive root-cause resolution, and automate manual processes

18Document data products, architectural decisions, and design patterns

19Lead cross-team initiatives to enable GenAI capabilities through Amazon Quick Suite

Requirements

EducationBachelor's degree in computer science or equivalent

Nice to HaveOptional

Kafka

Domain

AI-powered commercee-commerce

LeadershipMentoring or team leadership preferred