Job ID: VU-DSA (99590430)
Hybrid/Local Data Engineer/Data Solutions Architect (12+) with AI/ML, AWS, Kubernetes, data API, Docker, Elastic search, Redis, Vector stores, Python, SQL, Unix/Linux, Graph DB/neo4j, Starburst, RESTful, PostgreSQL, UI/UX, Jenkins, Agile experience
Location: Chicago, IL (Onsite – once a week)
Duration: 12 months
Client: Virtusa (End client: Baxter)
Required: I94 Travel History/LinkedIn profile
Note: We are not looking for data architects who implemented lakehouse, we are looking for full stack architects with Kubernetes first experience who have built scalable data APIs and deployed them as docker containers on Kubernetes. They should have exposure to databases like Elastic search, Redis etc.
Designing data solutions
Vector stores
Elastic search
Machine Learning
CUDA
GPU
Python Development
AI/ML
Responsibilities:
Design and implement the pipelines and endpoints that expose data to the enterprise.
Design and implement data pipelines using Python, SQL, and Unix to ensure data quality and integrity.
Work with Docker to containerize data pipelines and ensure scalability and portability.
Collaborate with cross-functional teams to gather requirements and integrate data analytics into business operations.
Ensure data privacy and security by implementing appropriate controls and protocols
Stay up-to-date with emerging trends and technologies in data analytics and machine learning.
Skills:
Experience in designing data solutions – data product/pipeline with full stack (python, docker, Kubernetes, API) etc. that follows interoperability guidelines
Proficient in use of Architectural patterns (“side cars”, Singleton, Pub/Sub, etc)
Expertise in Python web development and ML
Docker, Kubernetes
Unix (or Linux)
AWS or any cloud technologies
Graph DB (neo4j) or Vector Store (ElasticSearch, Redis)
[nice to have] Starburst, RESTful Endpoints, API, SQL, PostgreSQL, UI/UX, Jenkins, Agile