As a Data Engineer, responsibilities include designing, building, and maintaining scalable data infrastructure and pipelines to enable data-driven decision making across the organization.
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related technical field
- Proficiency in programming languages such as Python, Java, and SQL with experience in relevant data processing libraries and frameworks
- Strong understanding of data modeling, ETL/ELT processes, and data warehouse concepts
- Experience with cloud data platforms (AWS, Azure, GCP) and their data services (S3, Redshift, Big Query, Databricks, etc.)
- Hands-on experience with data pipeline orchestration tools (Airflow, Prefect, Dragster, or similar)
- Strong knowledge of both relational and NoSQL databases, data lakes, and data warehousing solutions
- Excellent problem-solving skills with the ability to troubleshoot complex data pipeline issues
- Ability to think critically about data architecture and design scalable, maintainable solutions
- Strong analytical skills and attention to detail to ensure data quality and accuracy
- Ability to collaborate effectively with cross-functional teams including data scientists, analysts, and business stakeholders
- Experience with version control systems (Git) and CI/CD practices for data pipelines
- Familiarity with streaming platforms (Kafka, Kinesis) and real-time data processing is a plus
- Knowledge of data governance, security best practices, and compliance requirements
- Overall 10+ year Engineering experience in building data-driven applications and 2+ years as promote engineer
Benefits
- Competitive salary
- Benefits to support your mental, physical, financial and social wellbeing
- Core bank funding for retirement savings, medical and life insurance
- Time-off including annual leave, parental/maternity leave, sabbatical, and volunteering leave
- Flexible working options
- Proactive wellbeing support
- Continuous learning culture to support your growth