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.