Hiring for Genpact – Data Architect | Band 4D

Company: Genpact

Payroll: Quess Corp

Location: Bangalore – Mandatory

Experience: 12+ Years – Mandatory
Primary Skills

SQL | Amazon Redshift | PySpark | AWS Glue | Vector Databases | Embeddings | Python | AWS Data Services
Job Summary

Lead the design and implementation of enterprise-scale data pipelines and embedding frameworks using AWS Glue, PySpark, Redshift, and Vector Databases. Drive AI-ready data ingestion, embedding generation, vector indexing, semantic search enablement, and high-performance data processing solutions.
Key Responsibilities
Design, build, and optimize batch and incremental data pipelines using PySpark and AWS Glue.
Develop embedding pipelines for structured and unstructured data using contemporary AI/LLM frameworks.
Build and manage Vector Database solutions for semantic search, RAG, and AI use cases.
Design ingestion frameworks for documents, APIs, databases, and streaming sources.
Optimize Redshift data models, SQL workloads, and large-scale analytical processing.
Implement data quality, monitoring, lineage,



and pipeline reliability controls.
Lead technical delivery, code reviews, and mentoring of engineering team members.
Required Experience

12+ years of experience in Data Engineering – Mandatory*

Bangalore location – Mandatory*
Robust expertise in SQL, Redshift, PySpark, AWS Glue, and Python.
Hands-on experience building embedding pipelines and Vector Database solutions.
Experience supporting RAG, semantic search, and AI/GenAI data platforms.
Proven experience leading technical initiatives and mentoring engineers.
Preferred Certifications
AWS Certified Data Engineer
AWS Certified Solutions Architect
Databricks Certified Data Engineer
Generative AI Certification
Focus Areas

Embedding Frameworks | Vector Databases | Data Pipelines | AWS Glue | PySpark | Redshift | Semantic Search | RAG Architecture | AI Data Engineering | Technical Leadership

Interested candidates can share their updated profile.

Pay: Up to ₹2,300,000.00 per year

Work Location: In person

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