Job Description
Cloudera Solution Architect
Job location - Pune/Nagpur (WFO)
Experience - 8+ Years
Key Responsibilities (Solution Architect)
Define and own the end-to-end architecture for AI-ready data platforms using Cloudera CDP , Spark, Kafka, Ni Fi, Hive, and Impala
Design scalable and reusable data ingestion, processing, and feature engineering frameworks to support advanced analytics and ML workloads
Architect and standardize MLOps platforms , including CI/CD pipelines, model deployment, scoring, monitoring, drift detection, and retraining strategies
Enable Gen AI and Retrieval-Augmented Generation (RAG) use cases by designing enterprise data preparation, embedding pipelines, and semantic data layers
Establish data quality, lineage, governance, and audit frameworks aligned with banking and regulatory requirements (AML, Risk, Compliance)
Partner with Data Science, AML, Risk, Fraud, and Digital Banking teams to translate business use cases into production-grade data and ML architectures
Drive performance optimization, scalability, resiliency, and cost efficiency across big-data and AI platforms
Define reference architectures, best practices, and standards for data, AI, and ML platforms
Provide architectural guidance, design reviews, and technical mentorship to engineering teams
Support presales, solutioning, and stakeholder discussions , including architecture walkthroughs and roadmap planning
Required Skills & Experience
Deep hands-on and architectural experience with Cloudera CDP (Public/Private Cloud)
Strong expertise in Spark (Py Spark/Scala), Kafka, Hive, Impala , and orchestration tools ( Airflow, Ni Fi )
Solid understanding of AI/ML platforms , feature stores, and end-to-end ML lifecycle
Experience designing solutions for banking and financial datasets , including AML, Fraud, Risk, Credit, and Customer Analytics
Strong knowledge of data governance, lineage, security, and compliance in regulated environments
Ability to translate complex business problems into scalable technical architectures
Excellent communication and stakeholder management skills
Preferred Skills
Experience with Gen AI architectures , RAG pipelines, vector databases, and LLM integration
Exposure to modern data architectures (lakehouse, streaming-first, event-driven)
Knowledge of MLOps tools, CI/CD, and platform automation
Prior experience in financial services or banking domain as an architect
Job location - Pune/Nagpur (WFO)
Experience - 8+ Years
Key Responsibilities (Solution Architect)
Define and own the end-to-end architecture for AI-ready data platforms using Cloudera CDP , Spark, Kafka, Ni Fi, Hive, and Impala
Design scalable and reusable data ingestion, processing, and feature engineering frameworks to support advanced analytics and ML workloads
Architect and standardize MLOps platforms , including CI/CD pipelines, model deployment, scoring, monitoring, drift detection, and retraining strategies
Enable Gen AI and Retrieval-Augmented Generation (RAG) use cases by designing enterprise data preparation, embedding pipelines, and semantic data layers
Establish data quality, lineage, governance, and audit frameworks aligned with banking and regulatory requirements (AML, Risk, Compliance)
Partner with Data Science, AML, Risk, Fraud, and Digital Banking teams to translate business use cases into production-grade data and ML architectures
Drive performance optimization, scalability, resiliency, and cost efficiency across big-data and AI platforms
Define reference architectures, best practices, and standards for data, AI, and ML platforms
Provide architectural guidance, design reviews, and technical mentorship to engineering teams
Support presales, solutioning, and stakeholder discussions , including architecture walkthroughs and roadmap planning
Required Skills & Experience
Deep hands-on and architectural experience with Cloudera CDP (Public/Private Cloud)
Strong expertise in Spark (Py Spark/Scala), Kafka, Hive, Impala , and orchestration tools ( Airflow, Ni Fi )
Solid understanding of AI/ML platforms , feature stores, and end-to-end ML lifecycle
Experience designing solutions for banking and financial datasets , including AML, Fraud, Risk, Credit, and Customer Analytics
Strong knowledge of data governance, lineage, security, and compliance in regulated environments
Ability to translate complex business problems into scalable technical architectures
Excellent communication and stakeholder management skills
Preferred Skills
Experience with Gen AI architectures , RAG pipelines, vector databases, and LLM integration
Exposure to modern data architectures (lakehouse, streaming-first, event-driven)
Knowledge of MLOps tools, CI/CD, and platform automation
Prior experience in financial services or banking domain as an architect
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