IND - Senior Staff Engineer, Data
India GCC-Puppalaguda Village
INR 2500K-4000K (estimate) Senior-level Full Time
Tasks
- Build Retrieval-Augmented Generation architectures
- Collaborate with DevOps for deployment and operations
- Design and develop data domains and data products
- Design and develop knowledge graph solutions
- Design build and maintain real time data streaming pipelines
- Ensure reliability availability and scalability of data pipelines
- Generate and validate synthetic data for evaluation
- Implement AI driven data engineering productivity improvements
- Implement data and AI pipelines for structured semi structured and unstructured data
- Implement monitoring alerting and incident management for data systems
- Implement reliability engineering fault tolerance and disaster recovery
- Implement semantic layer with dynamic query translation
- Integrate RAG with enterprise data infrastructure
- Integrate semantic layer with AI and LLM platforms
- Lead data and AI engineering for large data ecosystem
- Lead prototypes and experiments for GenAI solutions
- Mentor junior engineers and lead communities of practice
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | AWS Kinesis | AWS Kinesis Data Streams | AWS Lambda | Amazon EC2 | Amazon Kinesis | Amazon Neptune | Amazon OpenSearch | Amazon OpenSearch Service | Amazon S3 | Apache Kafka | Azure | CI/CD | Cypher | Data Catalog | Data Governance | Data Lake | Data Lineage | Data Quality | Data Streams | Data fabric | DataMesh | Docker | DynamoDB | ELT | ETL | Google Cloud | Graph Databases | Kinesis Data Streams | Knowledge graphs | Kubernetes | Langchain | Langgraph | MongoDB | Neo4j | NoSQL | NoSQL Databases | OpenSearch | OpenSearch Service | Prompt engineering | PyTorch | Python | RAG Pipelines | RDF | Retrieval-Augmented Generation | SPARQL | SQL | Semantic Modeling | Snowflake | Spark Streaming | TensorFlow | Unstructured Data | Vector Databases
Education
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