Data Architect

Job Description

Required Qualifications

· 10 years of experience in data engineering, with at least 3 years focused on Generative AI technologies.

· Expertise in designing and architecting production-ready enterprise grade data pipelines.

· Strong knowledge of vector databases, graph databases, NoSQL, Document DBs , including design, implementation, and optimization. (e.g. AWS open search or GCP Vertex AI, neo4j etc. Mongo, Dynamo, CosmosDB etc.)

· Expertise in designing, loading, and querying NoSQL, graph databases.

· Extensive experience in processing and leveraging unstructured data for data applications.

· Strong programming skills in Python and knowledge of deep learning frameworks such as PyTorch or TensorFlow.

· Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).

· Excellent communication skills and ability to explain complex technical concepts to both technical and non-technical stakeholders.

Job Responsibilities

· Hands on experience designing and developing end-to-end data pipelines, from data ingestion to pipeline deployment and monitoring.

· Lead the architecture and implementation of complex agentic frameworks, ensuring best practices in software engineering and data integrations.

· Collaborate with cross-functional teams (Technology, Business, Platform etc.) to integrate data solutions into existing data products and services.

· Stay at the forefront of GenAI advancements and incorporate new technologies and methodologies into our systems.

· Mentor and guide junior data engineers and architects in best practices for development.

· Design and implement optimized RAG architectures and pipelines.

· Design and implement strategies for handling unstructured data in pipelines.

· Design and implement graph database solutions for complex data relationships.

· Integrate data pipelines with Snowflake data warehouse for efficient data processing and storage.

· Build POCs to compare and evaluate various emerging technologies around data and AI.

· Create prototypes to establish patterns.