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Lead Data Engineer Hybrid Contract

This role is for a Lead Data Engineer on a hybrid contract, focusing on Azure and SSIS in the reinsurance industry. Key requirements include proficiency in Azure data services, ETL processes, and team leadership. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
💰 - Day rate
Unknown
Unknown
🗓️ - Date discovered
February 22, 2025
🕒 - Project duration
Unknown
🏝️ - Location type
Unknown
📄 - Contract type
Unknown
🔒 - Security clearance
Unknown
📍 - Location detailed
Bridgewater, NJ
🧠 - Skills detailed
#Data Governance #PySpark #Azure Blob Storage #Compliance #Azure Data Factory #Microsoft Power BI #Scala #"ETL (Extract #Transform #Load)" #Azure #SQL (Structured Query Language) #Data Pipeline #BI (Business Intelligence) #Azure Cosmos DB #Leadership #Azure SQL Database #Data Integration #Data Warehouse #DevOps #Automation #Computer Science #Spark (Apache Spark) #ADF (Azure Data Factory) #Python #Data Lake #API (Application Programming Interface) #Storage #Data Architecture #SSIS (SQL Server Integration Services) #Data Management #Security #Data Engineering #Data Processing #Azure SQL
Role description
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We are seeking a highly skilled Lead Data Engineer to join our global reinsurance team. This role focuses on leveraging cutting-edge technologies, including Azure and SSIS architectures, to support underwriting, claims analysis, and risk management. You will design and implement scalable data solutions, ensuring seamless data integration, availability, and security across systems and teams in a collaborative, global environment.

Key Responsibilities
• Design and Implement Data Solutions: Lead the design, implementation, and management of data solutions on Azure, including data pipelines, storage solutions, and data processing workflows.
• Data Architecture: Develop and maintain data architecture to support business requirements, ensuring scalability, performance, and cost-efficiency.
• Team Leadership: Manage and mentor a team of data engineers, providing guidance and support to ensure efficient data processes.
• Data Integration and ETL: Oversee the development and implementation of ETL processes to integrate data from various sources into data warehouses or data lakes or data stores.
• Performance Optimization:
• Continuously optimize data workflows, pipelines, and storage for performance, reliability, and fault tolerance.
• Monitor, troubleshoot, and resolve issues in data pipelines and systems proactively.
• Process Improvement: Identify and implement internal process improvements, such as automating manual processes and optimizing data delivery.
• Collaboration:
• Work closely with stakeholders and other teams to address data-related technical issues and support data-driven decision-making.
• Work with IT and compliance teams to ensure adherence to data governance, security, and privacy standards.
• Innovation and Automation
• Evaluate and implement modern data engineering tools and practices to enhance operational efficiency.
• Automate repetitive tasks to streamline processes and improve productivity.

Skills And Qualifications
• Educational Background
• Bachelor’s or master’s degree in computer science, Data Engineering, or a related field.
• Technical Skills
• Proficiency in Azure data services (e.g., Azure SQL Database, Azure Data Factory, Azure Cosmos DB, Azure Blob Storage).
• Hands-on experience with PySpark/Python, SQL
• Strong experience with SSIS.
• Solid understanding of Change Data Capture (CDC) techniques for incremental data processing.
• Familiarity with CI/CD tools such as DevOps.
• Familiarity in Data Fabric technologies and architectures and Azure data lake.
• Familiarity in Power BI for creating dynamic dashboards and reports.
• Familiarity with restful API and API integrations.
• Data Management: Strong knowledge of data management, data integration, and ETL processes.
• Leadership Skills: Proven experience in leading and managing a team of data engineers. Ability to handle multiple tasks and meet deadlines in a dynamic environment.
• Analytical Skills: Excellent analytical and problem-solving skills to transform raw data into actionable insights.
• Communication: Strong communication skills to effectively collaborate with stakeholders and team members.

Industry Knowledge
• Familiarity with the reinsurance/insurance domain, including risk modeling, claims analysis, and underwriting processes.

Required Skills : Data Warehouse

Basic Qualification

Additional Skills :

Background Check : No

Drug Screen : No