Data Engineer

The Data Engineer is responsible for designing, building, and maintaining data pipelines, models, ETL (Extract, Transform, Load) processes and other data infrastructure to support the organization's data needs. The role collaborates with data scientists and analysts to understand data requirements and develops scalable solutions. They build and optimize data pipelines, integrating data from various sources, ensuring data quality and consistency, and implement data governance practices.

What will your job entail?

Responsibilities:

• Designs, builds, and maintains scalable data pipelines to ingest, process, and transform data from various internal and external sources.
• Develops and maintains data warehouses or data lakes to store structured and unstructured data efficiently, ensuring data accessibility and reliability for analytics and reporting purposes.
• Integrates data from disparate systems sources, ensuring consistency, accuracy, and reliability of data across different platforms and applications within the organization.
• Conducts data modeling and database design, using cloud-based technologies and conducts dimensional modeling for data warehouses and data marts.
• Optimizes data processing and query performance to ensure timely and efficient data retrieval and analysis, utilizing techniques such as indexing, partitioning, and query optimization.
• Manages and maintains data infrastructure components such as databases, data warehouses, and cloud-based services, ensuring high availability, scalability, and performance.
• Implements data governance policies and procedures to ensure compliance with regulatory requirements and data security measures to protect sensitive information.
• Implements data quality checks and processes to identify and rectify data anomalies, inconsistencies, and errors, and ensures data integrity for downstream analytics and reporting.
• Participates in cross-functional teams to develop innovative data-driven solutions that improve operational efficiency, risk assessment, and customer experience in the insurance industry.
• Partners with data analysts, data scientists, and data consumers across IT and the business to optimize data availability and builds, refines, and enhances AI/ML models and algorithms.
• Stays up to date with new technologies and industry trends in data management and big data technologies.

Education:

• Bachelor’s degree in Computer Science, Information Technology or Engineering is required. Master’s degree preferred.

Licenses & Certifications:

• Prescribed: Not Applicable
• Preferred: Advanced Data Analytics Certifications (ADAC), SAS Statistical Business Analyst Professional Certification (SBAPC), Cloudera Certified Professional (CCP) Data Engineer