Data Engineer

Job SummaryWe are seeking a skilled and motivated Data Engineer to join a Specialty Insurance Firm. In this role, you will be responsible for building, maintaining, and optimizing the data infrastructure and pipelines to support advanced analytics, risk modeling, and data-driven decision-makingKey ResponsibilitiesData Pipeline Development: Design, build, and maintain scalable data pipelines to efficiently process, transform, and load data from multiple sources into our data lake or data warehouse.Data Integration: Integrate diverse data sources such as claims data, underwriting data, and third-party data for comprehensive analytics and reporting.Data Quality & Governance: Implement robust data quality checks and governance standards to ensure data accuracy, consistency, and compliance with industry regulations.Database Management: Develop, optimize, and manage data storage solutions using cloud-based platforms (e.g., AWS, Azure, or GCP) and relational or NoSQL databases.Collaboration with Stakeholders: Work closely with data scientists, actuaries, and business analysts to understand data requirements and support analytics initiatives.Automation: Automate repetitive data workflows, ensuring timely data availability and minimizing manual interventions.Data Security: Maintain data security protocols and collaborate with IT to safeguard sensitive insurance data in line with regulatory standards.Documentation: Document data processes, pipeline configurations, and database designs to ensure maintainability and transparency.QualificationsEducation: Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related field.Experience: 3+ years of experience as a Data Engineer, preferably within the insurance or financial services sector.Technical Skills:Proficiency in SQL, Python, and data pipeline tools (e.g., Apache Spark, Kafka, Airflow).Experience with cloud platforms like AWS (Redshift, S3, Glue), Azure (Synapse, Data Factory), or Google Cloud (BigQuery, Cloud Dataflow).Familiarity with ETL tools (e.g., Informatica, Talend, Alteryx) and data warehousing concepts.Knowledge of data modeling, data lakes, and data warehouse architecture.Strong understanding of API integrations and data streaming technologies.Industry Knowledge: Experience in or knowledge of the insurance sector, particularly with claims, underwriting, and actuarial data, is a plus.Analytical Skills: Ability to work with large datasets and drive meaningful insights and solutions for business stakeholders.Communication: Excellent written and verbal communication skills to explain complex technical concepts to non-technical teams.Nice to HaveExperience with machine learning frameworks and deployment of models in production.Knowledge of data visualization tools (e.g., Tableau, Power BI) to create actionable dashboards.Certification in cloud computing (AWS Certified Data Analytics, Google Professional Data Engineer, etc.).