Description
We are seeking a highly skilled and motivated Senior Data Engineer to join our dynamic team. The ideal candidate is a strong team player who can also lead, and who takes ownership of building, implementing, and maintaining robust data pipelines and data products that support our business objectives. This role blends strong engineering skills with a product mindset - ensuring data integrity, optimizing data workflows, working with big data at scale, and using modern AI tools to work faster and smarter. Financial-industry knowledge is not required for this role, but it is a plus.
Your Day-to-Day
- Design, develop, and maintain scalable, big-data pipelines and ETL/ELT processes.
- Implement and maintain data models, schemas, and documentation, ensuring they are built efficiently, reliably, and are well documented.
- Collaborate with product managers, analysts, and other stakeholders to understand data requirements and translate business needs into technical requirements.
- Ensure data quality and integrity across various data sources, and build monitoring around it.
- Design and implement data solutions end-to-end - from architecture and integration through delivery of production-grade data products.
- Optimize pipeline performance and troubleshoot complex issues.
- Use AI tools as part of the daily workflow (with an emphasis on Claude) to speed up development, automate repetitive work, and improve output quality.
- Stay updated with the latest industry trends and best practices in data engineering, big data, and AI-assisted development.
Requirements
- Proven experience as a Data Engineer - at least 3-5 years.
- Expert proficiency in SQL.
- Advanced programming skills in Python.
- Hands-on experience with big data technologies and end-to-end development of data products.
- Proven experience designing data solutions and architectures (data-model/schema design is not required for this role).
- Experience developing data monitoring processes.
- Hands-on experience with cloud data platforms (Snowflake, OCI, or similar).
- Understanding of Kafka and event-driven architectures for real-time data processing.
- Practical experience working with AI tools as part of the development process, with an emphasis on Claude.
- Proven experience with cloud architecture principles.
- Strong communication and collaboration skills.
- Advanced troubleshooting skills - excellent problem-solving, attention to detail, and the ability to analyze complex data structures
Advantages
- Experience in the banking or fintech industry, and familiarity with financial data models, accounting principles, and regulatory reporting.
- Experience with API integrations and financial transaction data processing.
- Exposure to machine learning and predictive analytics in financial risk modeling.
- Experience with data visualization and BI tools (Power BI, Looker, or similar).
