Data Engineer (Life - Insurance)

OverviewWe are looking for a Data Engineer who can build a solid data foundation and convert business requirements into meaningful insights. This role combines data engineering (ETL, data models, automation) and analytics (requirement gathering, translating into technical specifications, and delivering insights) to ensure efficient and reliable data flow to support strategic and operational decision-making across the insurance business.Key ResponsibilitiesData EngineeringDesign, build, and maintain ETL pipelines to consolidate data from multiple sources into a single source of truth.Develop and maintain logical and physical data models (customer, policy, premium, claims, and agents/commissions).Perform data cleansing and validation to ensure accuracy, consistency, completeness, and readiness for reporting.Automate recurring business reports and dashboards to reduce manual effort and ensure timely availability of insights.Monitor data workflow and continuously improve data availability and data quality.Maintain database-related documentation including architecture diagrams and procedures.Data Analytics & InsightsWork with stakeholders to gather data/reporting requirements and translate them into technical specifications. Build dashboards and analytical views that support business monitoring and operational decisions.Work closely with business stakeholders to identify opportunities for process improvement through data-driven insights. Conduct ad-hoc analysis to support strategic decisions.QualificationsBachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Information Systems, or a related field.Minimum 3-5 years of experience in data engineering, analytics, or business intelligence.Strong experience working with large datasets and relational data modeling.Strong proficiency in SQL (advanced level), relational databases (e.g., MySQL, PostgreSQL, SQL Server) and strong ETL/ELT experience (SSIS, Informatica, Airflow, etc.).Proficiency in BI tools (e.g., Power BI, Tableau, Looker). Experience with Python, R, or other programming languages for data analysis is a plus.Knowledge of insurance business models, policy data, and financial reporting. Ability to translate complex data into business-friendly insights. Excellent analytical thinking, problem-solving, communication, collaboration skills, ability to work independently and manage multiple priorities in a fast-paced environment.Good command in both written and spoken English