Data Engineer

Key Responsibilities: Solutions Delivery & Implementation: • Design and implement new technical solutions that meet the business requirements and technical specifications. • Perform technical assessments and support the delivery of solutions, ensuring all deadlines and quality standards are met. Collaboration with Stakeholders: • Build strong relationships with internal and external stakeholders to drive client satisfaction. Maintain ongoing communication to ensure that requirements are fully understood and reflected in the delivered solutions. • Provide regular updates on project progress, issues, and milestones. System & Process Optimization: • Participate in reviews and assessments of existing systems to identify areas for improvement, optimization, and re-engineering. • Proactively contribute to the evolution of system architecture, recommending improvements based on business needs and industry trends. Agile Development: • Work within an agile framework, participating in planning, stand-ups, and reviews to ensure timely delivery of solutions. Troubleshooting & Issue Resolution: • Investigate and resolve technical issues that arise during both the implementation and operational phases of a project. • Provide post-implementation support, ensuring that any issues are quickly identified and resolved, minimizing disruption to business operations. Documentation & Knowledge Sharing: • Create and maintain comprehensive technical documentation, which may include code, processes, system architecture diagrams and integration specifications. • Share knowledge and expertise with team members, promoting best practices and fostering a culture of collaborative learning. Continuous Learning & Innovation: • Stay up to date with emerging technologies and best practices to improve solution delivery. Code Quality and Best Practices: • Write clean, efficient, and maintainable code, adhering to coding standards and best practices. Participate in code reviews to maintain high-quality standards. Testing and Debugging: • Implement data validation checks, monitor data quality, and address any issues related to data integrity and accuracy. • Develop unit tests, conduct functional and integration testing, and debug issues to ensure reliability and stability. Qualifications: • Bachelor's degree or equivalent experience • 6-10 years of experience • Highly Preferred: o Experience in the insurance/financial industry o AWS Cloud Practitioner Certification • AWS: Glue, Step Functions, Lambda, Batch, S3, DynamoDB • Proficiency in Excel, SQL Server (queries, SSIS, SSRS), and ETL (Extract, Transform, Load) processes for supporting legacy solutions. • GitHub • Experience with project management software (e.g., Jira). • Expertise in Agile methodologies (e.g., Kanban, Scrum) for managing delivery • Understanding of SDLC processes, best practices, testing, deployment, and version control systems. • Experience ensuring secure data handling, especially sensitive financial data and personally identifiable information (PII). • Proficient in data validation and data cleansing practices.