Solution Architect (Data modernization| Cloud Architect |Data & Analytics)

Overview

On Site
Full Time

Skills

MDM
Data Governance
CLOUD
ANALYTICS
AI
big data
data pipeline
Master Data Management
Enterprise Data Architecture
Data Analytics Platform
analytics solutions
modernizing data resources
data ingestion
data stewardship
metadata management

Job Details

Dear Applicant,

Please let me know if you are interested.

Job Role Solution Architect (Data modernization| Cloud Architect |Data & Analytics)

Location Mount Laurel, NJ (Onsite)

Job type: Fulltime

Requirement:

Design and architect scalable, secure, and high-performance cloud and data solutions on Microsoft Azure, with added leadership to Drive end-to-end delivery of data and analytics programs, integrating Databricks, modern data platform patterns, and production-grade
Key Responsibilities
Architect scalable, secure, and high-performance solutions using Microsoft Azure services, incorporating Gen-Al and LLM components where appropriate.
Create detailed architecture blueprints, solution diagrams, and technical documentation for cloud, data solutions.
Design large-scale data processing and analytics platforms leveraging Azure Databricks and Apache Spark.
Lead the implementation of Databricks-based and Azure-based solutions, ensuring they follow best practices and meet business requirements.
Lead design and delivery of Gen-AVLLM solutions including use cases such as summarization, question-answering, knowledge augmentation, generation, and intelligent automation.
Design and implement CI/CD and MLOps practices for data pipelines and model lifecycle management using Azure DevOps and Azure ML. capabilities.
Provide technical leadership and guidance across the project lifecycle, including prompt engineering best practices, safety and hallucination mitigation strategies, and model governance.
Ensure robust security, privacy, and compliance measures for Gen-Al and data solutions, including identity management, encryption, Pil handling, and access controls.
Optimize cloud and model-serving resources for performance, cost, and reliability, including scalable inference, batching, and autoscaling strategies.
Monitor model performance and data pipelines in production, establish alerting and metrics for accuracy, bias, latency, and cost.
Collaborate with stakeholders to gather requirements, translate them into technical solutions, and advocate responsible use of Gen-Al.
Stay current with the latest Azure services (including Azure OpenAl Service, Cognitive Services), LLM developments, and industry trends to recommend improvements.
Requirements
Bachelor's degree in Computer Science, Engineering, or a related field.
15+ years of experience in data engineering, cloud architecture, or a closely related discipline.
Deep hands-on experience with Databricks and Apache Spark.
Familiarity with Azure OpenAl Service, Azure Cognitive Services, or equivalent managed ML/LLM platforms.
Strong proficiency in Python.
Solid SQL skills and experience with relational and analytical databases.
Proven experience with cloud platforms, with a strong focus on Microsoft Azure.
Experience with modern data warehousing patterns and technologies (eg, Delta Lake, Lakehouse architectures).
Understanding of data governance, privacy, security best practices, and ethical considerations for Gen-Al. Experience implementing MLOps for model versioning, CI/CD for models, automated testing, and monitoring

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