All fields marked * are required
AWS Data Architect – AI & GenAI
Location: Bengaluru
Work Mode: Work from Office – 5 Days a Week
Experience: 8+ Years
Employment Type: Full-Time
Budget: ₹30–45 LPA
Job Overview
We are looking for an experienced AWS Data Architect to design and build scalable, secure, and enterprise-grade data platforms on AWS. The ideal candidate should have strong expertise in data architecture, AWS data services, Spark, data modelling, and modern AI/GenAI technologies including RAG, embeddings, and vector search.
This is a senior technical role requiring hands-on architecture ownership, strong problem-solving skills, and the ability to work closely with engineering and business stakeholders.
Key Responsibilities
Design and own end-to-end data architecture on AWS, including data lakes, lakehouse and data warehouse solutions.
Design data ingestion, storage, processing, compute, and data modelling strategies.
Architect solutions using AWS services such as S3, Glue, Lake Formation, EMR, Athena, Redshift, Kinesis/MSK, Lambda, Step Functions, DynamoDB, RDS, and Aurora.
Build and define data foundations for AI and GenAI applications, including embedding pipelines, vector databases, retrieval strategies, and evaluation datasets.
Design and support GenAI workloads using Amazon Bedrock, SageMaker, or similar platforms.
Develop and implement RAG architectures, embeddings, vector search, prompt/context design, and LLM application patterns.
Establish data governance, security, and compliance standards including IAM, encryption, KMS, PII handling, data classification, lineage, and auditing.
Define architecture standards, reference architectures, data contracts, naming conventions, and data modelling practices.
Optimize cloud infrastructure and data workloads for performance and cost.
Work with stakeholders and engineering teams to understand requirements and translate them into scalable technical solutions.
Review technical designs and mentor Data Engineers and ML Engineers.
Contribute to infrastructure automation, CI/CD, and architecture best practices.
Mandatory Skills & Experience
8+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.
Minimum 4+ years of hands-on experience designing and architecting data platforms on AWS.
Strong hands-on experience with AWS data services:
Amazon S3
AWS Glue
AWS Lake Formation
Amazon EMR / Spark
Amazon Athena
Amazon Redshift
Amazon Kinesis or MSK
AWS Lambda
AWS Step Functions
Strong experience designing and delivering large-scale production data platforms.
Strong knowledge of data modelling, including:
Dimensional Modelling
Data Vault
Lakehouse Architecture
Expert-level SQL skills.
Strong hands-on experience with Apache Spark.
Experience with at least one lakehouse table format:
Apache Iceberg
Delta Lake
Apache Hudi
Strong Python programming skills.
Experience with Infrastructure as Code using Terraform or AWS CDK.
Experience implementing CI/CD pipelines for data platforms.
Working knowledge of AI/GenAI engineering, including:
LLM application patterns
RAG architectures
Embeddings
Vector search
Prompt engineering
Context design
Evaluation of LLM/GenAI applications
Strong understanding of AWS security and governance:
IAM
KMS
VPC
Encryption
Data security and access controls
Experience working with compliance or data governance standards such as SOC 2, ISO 27001, HIPAA, GDPR, or DPDP.
Strong communication and stakeholder management skills.
Preferred Skills
Experience with Amazon Bedrock or Amazon SageMaker.
Experience with agentic AI or AI frameworks such as LangGraph, LlamaIndex, CrewAI, Strands, or similar.
Experience with Snowflake or Databricks.
Experience with real-time and streaming data architectures using Flink, Spark Structured Streaming, Kinesis, Kafka, Debezium, or AWS DMS.
Experience with Kubernetes or Amazon EKS.
AWS certifications such as AWS Certified Data Engineer, AWS Solutions Architect – Professional, or Machine Learning certification.
Experience with cloud migration or multi-cloud environments.
Experience in solution architecture, technical consulting, or pre-sales is an added advantage.
Ideal Candidate
The ideal candidate is a hands-on AWS Data Architect with strong experience designing enterprise-scale data platforms and the ability to combine modern data engineering with AI/GenAI architecture. The candidate should be comfortable making architecture decisions, reviewing technical solutions, solving complex engineering challenges, and working closely with senior stakeholders.
Location: Bengaluru
Work Mode: Work from Office – 5 Days a Week
Experience: 8+ Years
CTC: ₹30–45 LPA
Required
Preferred
All fields marked * are required
AWS Data Architect – AI & GenAI
Location: Bengaluru
Work Mode: Work from Office – 5 Days a Week
Experience: 8+ Years
Employment Type: Full-Time
Budget: ₹30–45 LPA
Job Overview
We are looking for an experienced AWS Data Architect to design and build scalable, secure, and enterprise-grade data platforms on AWS. The ideal candidate should have strong expertise in data architecture, AWS data services, Spark, data modelling, and modern AI/GenAI technologies including RAG, embeddings, and vector search.
This is a senior technical role requiring hands-on architecture ownership, strong problem-solving skills, and the ability to work closely with engineering and business stakeholders.
Key Responsibilities
Design and own end-to-end data architecture on AWS, including data lakes, lakehouse and data warehouse solutions.
Design data ingestion, storage, processing, compute, and data modelling strategies.
Architect solutions using AWS services such as S3, Glue, Lake Formation, EMR, Athena, Redshift, Kinesis/MSK, Lambda, Step Functions, DynamoDB, RDS, and Aurora.
Build and define data foundations for AI and GenAI applications, including embedding pipelines, vector databases, retrieval strategies, and evaluation datasets.
Design and support GenAI workloads using Amazon Bedrock, SageMaker, or similar platforms.
Develop and implement RAG architectures, embeddings, vector search, prompt/context design, and LLM application patterns.
Establish data governance, security, and compliance standards including IAM, encryption, KMS, PII handling, data classification, lineage, and auditing.
Define architecture standards, reference architectures, data contracts, naming conventions, and data modelling practices.
Optimize cloud infrastructure and data workloads for performance and cost.
Work with stakeholders and engineering teams to understand requirements and translate them into scalable technical solutions.
Review technical designs and mentor Data Engineers and ML Engineers.
Contribute to infrastructure automation, CI/CD, and architecture best practices.
Mandatory Skills & Experience
8+ years of experience in Data Engineering, Data Platform Engineering, or Data Architecture.
Minimum 4+ years of hands-on experience designing and architecting data platforms on AWS.
Strong hands-on experience with AWS data services:
Amazon S3
AWS Glue
AWS Lake Formation
Amazon EMR / Spark
Amazon Athena
Amazon Redshift
Amazon Kinesis or MSK
AWS Lambda
AWS Step Functions
Strong experience designing and delivering large-scale production data platforms.
Strong knowledge of data modelling, including:
Dimensional Modelling
Data Vault
Lakehouse Architecture
Expert-level SQL skills.
Strong hands-on experience with Apache Spark.
Experience with at least one lakehouse table format:
Apache Iceberg
Delta Lake
Apache Hudi
Strong Python programming skills.
Experience with Infrastructure as Code using Terraform or AWS CDK.
Experience implementing CI/CD pipelines for data platforms.
Working knowledge of AI/GenAI engineering, including:
LLM application patterns
RAG architectures
Embeddings
Vector search
Prompt engineering
Context design
Evaluation of LLM/GenAI applications
Strong understanding of AWS security and governance:
IAM
KMS
VPC
Encryption
Data security and access controls
Experience working with compliance or data governance standards such as SOC 2, ISO 27001, HIPAA, GDPR, or DPDP.
Strong communication and stakeholder management skills.
Preferred Skills
Experience with Amazon Bedrock or Amazon SageMaker.
Experience with agentic AI or AI frameworks such as LangGraph, LlamaIndex, CrewAI, Strands, or similar.
Experience with Snowflake or Databricks.
Experience with real-time and streaming data architectures using Flink, Spark Structured Streaming, Kinesis, Kafka, Debezium, or AWS DMS.
Experience with Kubernetes or Amazon EKS.
AWS certifications such as AWS Certified Data Engineer, AWS Solutions Architect – Professional, or Machine Learning certification.
Experience with cloud migration or multi-cloud environments.
Experience in solution architecture, technical consulting, or pre-sales is an added advantage.
Ideal Candidate
The ideal candidate is a hands-on AWS Data Architect with strong experience designing enterprise-scale data platforms and the ability to combine modern data engineering with AI/GenAI architecture. The candidate should be comfortable making architecture decisions, reviewing technical solutions, solving complex engineering challenges, and working closely with senior stakeholders.
Location: Bengaluru
Work Mode: Work from Office – 5 Days a Week
Experience: 8+ Years
CTC: ₹30–45 LPA
Required
Preferred