The Job

Data Engineer II, CMT

Technology, Data & Digital · Data, AI & Analytics · Data Engineering

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In short

As a Data Engineer II, you will be responsible for designing and architecting scalable data systems, leading technical initiatives at the intersection of data engineering and AI, and mentoring junior engineers. You will drive the development of AI-native infrastructure, data-as-a-product delivery, and AWS-based pipelines while ensuring operational excellence.

Responsibilities

  • Design and architect AI-native infrastructure supporting real-time data processing for AI/ML inference, training, and continuous learning at scale.
  • Lead the development of semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access.
  • Architect infrastructure for agentic AI systems with multi-agent orchestration.
  • Drive GenAI-powered data quality, entity resolution, and metadata management strategies.
  • Own end-to-end accountability for complex data products from ingestion to consumption, defining SLAs and driving adoption.
  • Lead the delivery of data products with measurable quality metrics and customer satisfaction targets.
  • Design and build self-service platforms with embedded governance, lineage, and discovery.
  • Define data contracts and API standards for reliable, versioned data consumption.
  • Architect and optimize AWS infrastructure: EC2, Lambda, S3, Redshift, EMR.
  • Design high-throughput, fault-tolerant pipelines supporting analysts, data scientists, and AI agents.
  • Lead implementation of CDC and event-driven architectures for sub-minute data availability.
  • Drive infrastructure-as-code best practices using CDK.
  • Mentor Data Engineer I team members, conducting code reviews and elevating engineering standards.
  • Own operational health of critical pipelines, driving root cause analysis and long-term prevention strategies.
  • Author and maintain technical design documents, influencing architectural decisions.
  • Lead peak readiness efforts and incident response.
  • Drive automation initiatives that reduce operational toil and enable non-linear scaling.

Requirements

  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Bachelor's degree

Desired 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)
#Data Engineering#AI#ML#ETL#SQL#AWS#Redshift#S3#Lambda#CDK#Business Intelligence
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Company

Amazon

Job Posted

1 month ago

Employment Type

Full Time

WorkMode

On Site

Experience Level

Mid-Senior

Locations

Bengaluru, India

Qualification

Bachelor

Applicants

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