Jersey City, NJ
Job Description
Bachelor's Degree (required) or Master's Degree (preferred) in Computer Science, Information Systems, or a related field
- 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.