As a Data Engineer, you will support the development of data-driven solutions that strengthen financial reporting, analytics, and business decision-making within the property and casualty (P&C) insurance sector. You will work closely with business stakeholders, product owners, and technology teams to translate business needs into clear technical and functional requirements. Your responsibilities will include data analysis, requirements documentation, business rule validation, and supporting user acceptance testing to ensure reliable, high-quality data solutions. You will also contribute to data integration strategies, reporting improvements, and the ongoing optimization of dashboards and data platforms. Working in a global, multicultural environment, you will help bridge the gap between business objectives and technical delivery. This remote opportunity is ideal for an analytical professional who combines insurance industry knowledge with strong SQL, Power BI, and data quality expertise.
Business Requirements Analysis: Gather, analyze, and document business requirements by collaborating with stakeholders, subject matter experts, product owners, and technology teams to understand reporting and analytics needs.
Functional Specifications and Documentation: Translate business data stories into clear, actionable functional specifications, business plans, and technical documentation that support successful data solution delivery.
Data Integration and Mapping: Support source-to-target mapping, data integration initiatives, and the use of data marts and data warehouses to improve reporting capabilities and downstream data consumption.
SQL and Power BI Analytics: Contribute to the development, enhancement, and maintenance of data-driven reporting solutions, dashboards, and analytics products that address evolving business requirements.
Data Quality and Business Rule Validation: Validate business rules, monitor data quality, troubleshoot discrepancies, and collaborate with technical teams to ensure data accuracy, consistency, and reliability.
User Acceptance Testing (UAT): Support UAT planning and execution, validate solution functionality against business requirements, track issues, and coordinate testing updates and approvals.
Cross-Functional Collaboration: Act as a liaison between business stakeholders, IT teams, and product management to ensure requirements are understood and implemented accurately.
Data Product Certification: Assist with data product certification and ensure solutions meet reporting standards, business expectations, data quality requirements, and downstream consumption needs.
Data Platform Optimization: Identify opportunities to improve data platforms, dashboards, reports, and integration processes in response to changing business needs and applicable guidelines.
Financial Data Governance and Compliance: Apply relevant data standards and practices to financial services transactions, reporting, and cloud-based data storage and sharing, balancing regulatory and compliance obligations with business objectives.
Project Coordination and Issue Resolution: Manage moderately complex data and analytics initiatives with limited supervision, maintain records of decisions and approvals, and proactively develop solutions to prevent or mitigate data-related issues.
Technical Support and Knowledge Sharing: Contribute to technical specifications, strategic planning, testing updates, training, and ongoing support to promote effective adoption of data solutions.