Data Engineer- Azure :: Jersey City, NJ (Hybrid)

Key Responsibilities:

- 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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.