Description
FBA is seeking a Data Engineer to help 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 supporting next-generation intelligent data platforms, this role is for you.
Core Responsibilities
AI-Native Infrastructure & Real-Time Processing
Support the development of AI-native infrastructure for real-time data processing supporting AI/ML inference, training, and continuous learning
Contribute to building semantic layers and knowledge graphs that enable intelligent query routing and context-aware data access
Assist in developing infrastructure components for agentic AI systems with multi-agent orchestration
Implement GenAI-powered data quality checks, entity resolution pipelines, and metadata management workflows
Data-as-a-Product Delivery
Contribute to end-to-end data product delivery from ingestion to consumption
Support data products with clear SLAs, quality metrics, and customer satisfaction measures
Help build self-service platforms with embedded governance, lineage, and discovery
Implement data contracts and APIs for reliable, versioned data consumption
AWS Infrastructure & Pipeline Engineering
Work with AWS resources: EC2, Lambda, S3, Redshift, Kinesis, EMR, SageMaker, Bedrock, Neptune
Build and maintain 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
3+ years in data engineering with cloud-native architectures
Working knowledge of AWS services (Redshift, S3, Glue, Kinesis, EMR)
Experience with real-time streaming technologies (Kafka, Kinesis, or Flink)
Exposure to AI/ML infrastructure (SageMaker, Bedrock)
Proficiency in Python, SQL, and familiarity with 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
Help build the foundational infrastructure powering next-generation AI-enabled data products at Amazon FBA.
Basic Qualifications
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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.
Company - ADCI - Karnataka
Job ID: A10446769
