Senior Data Engineering and Reporting Specialist

A Data and Reporting Engineer is responsible for collecting, transforming, and storing data from various sources, ensuring data quality and integrity, and creating meaningful reports and dashboards for stakeholders.

1. Data Extraction and Transformation:
   • Gather data from diverse sources, such as databases, APIs, and flat files.
   • Clean, transform, and preprocess data to ensure accuracy and consistency.
   • Develop and maintain ETL (Extract, Transform, Load) processes.
2. Data Warehousing:
   • Design and maintain data warehouses or data lakes to store and organize data efficiently.
   • Implement data modeling and schema design to optimize data retrieval.
   • Manage big data effectively.
3. Database Management:
   • Administer and optimize databases for performance and scalability.
   • Ensure data security and access control measures are in place.
4. Reporting and Visualization:
   • Create interactive dashboards and reports using tools like Tableau, Power BI, or custom solutions.
   • Collaborate with business analysts and stakeholders to define reporting requirements.
5. Data Quality and Governance:
   • Implement data quality checks and validation processes.
   • Establish data governance policies to maintain data integrity.
   • Perform root cause analysis on data queries from stakeholders.
6. Automation and Scalability:
   • Develop automated solutions for data processing and reporting tasks.
   • Scale data pipelines and reporting systems to handle growing data volumes.
7. Performance Monitoring:
   • Monitor system performance, troubleshoot issues, and optimize query performance.
   • Implement alerting mechanisms for system failures or anomalies.
8. Documentation and Knowledge Sharing:
   • Maintain documentation for data pipelines, data models, and reporting processes.
   • Collaborate with team members and stakeholders to share knowledge and best practices.
9. Technical Expertise:
   • Stay up-to-date with emerging technologies and best practices in data engineering and reporting.
   • Enhance skills in SQL, data modeling, and reporting tools.
10. Project Management:
    • Lead and manage onshore reporting project requirements and maintain direct contact with specific AO business units.
    • Implement Agile methodologies on various reporting projects.
11. Quality Assurance:
    • Implement data quality checks to ensure data integrity.
    • Identify and resolve data quality issues as they arise.
    • Audit reports produced by the team to ensure DTP adherence.

Knowledge:

• General knowledge of insurance business and market conditions preferred.
• Fundamental knowledge of data analysis, extraction, and management techniques for insurance portfolios.
• Strong mathematical and statistical knowledge.
• Knowledge in report template creation and design.
• Familiarity with Agile methodologies such as Scrum, Kanban, and Lean.

Skills:

• Proficiency in data modeling, SQL, and database management systems.
• Experience with ETL tools like SAS Base, SAS EG, Apache NiFi, Apache Spark, Talend.
• Knowledge of data warehousing technologies.
• Familiarity with reporting tools like Tableau, Power BI, QlikView.
• Programming skills in Python, Java, or Scala for data processing and automation.
• Strong analytical and problem-solving skills.
• Understanding of data governance and security principles.
• Excellent communication skills for effective cross-functional collaboration.
• Ability to adapt to evolving data engineering and reporting technologies.

• Minimum 7+ years in SAS Base, SAS EG, SQL, Excel, Tableau, Power BI, with involvement in automation initiatives.
• At least 1 year experience in the financial services industry, preferably insurance.
• Experience in consulting or shared services environment is preferred.

Bachelor's Degree in Computer Science, Information Technology, or related field, or equivalent work experience.

• Business Intelligence Applications, Business Management, Communication, Critical Thinking, Customer Service, Detail-Oriented, Financial Products, Stakeholder Management, etc.

Our ideal candidate has a solid foundation in data engineering and reporting, with expertise in data modeling, SQL, and database management. They possess excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams. Experience in automation and scalability is highly desirable.