Responsibbilities:
1. Data Pipeline Development: Design, implement, and maintain scalable data pipelines for the extraction, transformation, and loading of large datasets.
2. Data Modelling: Develop and optimize data models to support analytical and reporting requirements, ensuring data accuracy and reliability.
3. Data Integration: Integrate diverse data sources and formats to enable seamless data flow across systems.
4. Data Quality Assurance: Implement and monitor data quality checks to ensure the integrity of the data throughout the entire data lifecycle.
5. Collaboration: Work closely with business analysts, colleagues and other stakeholders to understand data requirements and deliver effective solutions.
6. Performance Optimization: Identify and address performance bottlenecks in data processing and storage systems.
7. Documentation: Document data engineering processes, data models, and configurations for knowledge sharing and future reference.
8. Adherence to Best Practices: Stay current with industry trends and best practices in data engineering within company and ensure the adoption of these practices within the team.
Requirements:
· Bachelor's degree in Computer Science, Information Technology, or a related field.
· Minimum of 5 years of proven experience as a Data Engineer or similar role.
· Strong proficiency in programming languages such as Spark SQL and Python in a HIVE environment.
· Familiarity with cloud platforms such as AWS and Big Data infrastructure, Jira, Bitbucket, etc.
· Experience in CI/CD pipeline and working in an Agile environment.
· Excellent problem-solving skills and attention to detail.
· Strong communication and collaboration skills.
· Knowledge of data warehousing concepts and technologies.
· Candidates with experience in the Banking Industry will have an added advantage.
· Ability to communicate effectively with multiple levels of management and summarize complex technical requests succinctly.
