Data and Reporting Engineer (POWER BI)

• 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.

• 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.

• Big data management

• Database Management:

• Administer and optimize databases for performance and scalability.

• Ensure data security and access control measures are in place.

• Reporting and Visualization:

• Create interactive dashboards and reports using tools like Tableau, Power BI, or custom-built solutions.

• Collaborate with business analysts and stakeholders to define reporting requirements**.**

• Data Quality and Governance:

• Implement data quality checks and validation processes.

• Establish data governance policies and procedures to maintain data integrity.

• Perform root cause analysis on data queries from stakeholders

• Automation and Scalability:

• Develop automated solutions for data processing and reporting tasks.

• Scale data pipelines and reporting systems to handle growing volumes of data.

• Performance Monitoring:

• Monitor system performance, troubleshoot issues, and optimize query performance.

• Implement alerting mechanisms for system failures or anomalies.

• 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.

• Technical Expertise:

• Stay up-to-date with emerging technologies and best practices in data engineering and reporting.

• Continuously enhance skills in SQL, data modeling, and reporting tools.

• Project Management:

• Leading and managing onshore reporting project requirements and direct contact of specific AO business units.

• Implement Agile methodology on different reporting projects

• Quality Assurance:

• Implement data quality checks to ensure data integrity.

• Identify and address data quality issues as they arise.

• Audit reports produced by the team ensuring DTP is adhered to.

QUALIFICATIONS:

Knowledge

• General knowledge of insurance business and related market conditions preferred

• Fundamental knowledge of data analysis, extraction and management techniques for insurance portfolios

• Strong mathematical and statistical knowledge

• Fundamental knowledge in Report template creation and design

• Agile methodologies, such as Scrum, Kanban, and Lean.

Skills

• Proficiency in data modeling, SQL, and database management systems (e.g., SQL Server, Oracle, PostgreSQL).

• Experience with ETL tools and processes (e.g.,SAS Base, SAS EG, Apache NiFi, Apache Spark, Talend).

• Knowledge of data warehousing concepts and technologies (e.g., Snowflake, Redshift, BigQuery).

• Familiarity with reporting and visualization tools (e.g., Tableau, Power BI, QlikView).

• Programming skills in languages such as Python, Java, or Scala for data processing and automation.

• Strong analytical and problem-solving skills.

• Understanding of data governance and data security principles.

• Excellent communication skills to work effectively with cross-functional teams and business stakeholders.

• Ability to adapt to evolving technologies and trends in data engineering and reporting.

Experience

• 7+ years minimum experience in SAS Base, SAS EG, SQL, Excel, Tableau, Power BI, Has been involved in multiple automation initiatives that delivered tangible benefits

• At least 1 year experience in the financial services industry, preferably in insurance

• Working experience in a consulting or shared services environment preferred

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