Location: Jersey City, NJ / ONSITE
Duration: Long Term Project
Experience: 15+
Client: Capgemini/End client
Job Description:
– 10+ years of overall technology experience strategizing, engineering, configuring and implementing software solutions and services
– 5+ years in the data engineering space with deep experience delivering enhanced analytic and data access capabilities
– Domain knowledge of the Insurance Industry (preferably P&C) and value chain as well as the technologies and solutions relevant to this industry is desired
– Hands-on knowledge of current technology standards/trends coupled with a desire to continually expand personal knowledge/skills
– Ability and interest in mentoring technical staff and raising our collective technical competencies
– Ability to establish and maintain relationships with other business and technology leaders
– Strong written and verbal communication skills coupled with the ability to tailor communication to all levels of an organization
– Open-minded with proven ability to work collaboratively with others in team environment
– Strong understanding of IT environments, technologies in relation to business needs
– Demonstrate strong ability to work in a team environment and foster cross-team collaboration
– Experience executing technology modernization initiatives including migration to cloud native and API Strategies
– Strong grasp of value creation and business capability models
– Deep experience architecting data and analytics capabilities within a complex multi-national organization that meet requirements for availability, resiliency, stability, scalability, and security.
– Current experience with Azure, APIs, accelerators, DevSecOps, Infrastructure as Code, Containers and Event driven messaging applications (Kafka, MQ)
– Experience in Azure Cloud technologies like ADLS, ADF, Databricks, Synapse Analytics is a huge plus
– Proficient use of tools, techniques, and manipulation including programming languages (Python, PySpark, SQL etc.), and an understanding of data engineering practices
– Experience implementing, developing and integrating Data Management Capabilities (Meta Data, MDM, Reference Data)
– Deep understand on the advanced analytics techniques using ML and AI
– Experience with the MLOps Tools like mlFlow, DVC (data version control) and other MLOps frameworks
– Experience in developing and maintaining CI/CD pipelines for automated deployment of ML models using Azure Devops and databricks webhooks.
– Experience in designing & managing data pipeline using ADF, Databricks and delta lake to ensure reliable data flow for model training and scheduling automated retraining.
– Experience in implementing model monitoring solution to track ML performance, detect data drift and setting up alerts for proactive maintenance and troubleshooting.
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Shahid Mohammad Sr Technical Recruiter |
2050 Center Avenue | Suite 600 | Fort Lee, NJ 07024 Direct Number: (201) 354-2896 tel (201) 242-5505 x121 shahid.m@wonese.com | www.wonese.com |
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