What are the responsibilities and job description for the Data Architect - Long Term Contract on W2 - Hybrid - Dallas, TX position at Montek System?
Job Details
Data Architect
Long Term Contract on W2
Dallas, TX (Hybrid, 2-3 days a week)
Key Skills DB Architecture, Azure, Cosmos DB, VectorDBs, PostgreSQL
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 Google Cloud Platform 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, Google Cloud Platform, 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.
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