About the Role
We are looking for a motivated Data Engineer to join our Data Management and AI team and contribute to building scalable data platforms that power analytics and AI initiatives across our digital banking ecosystem.
In this role, you will design and develop data pipelines, streaming infrastructure, and data warehouse solutions that enable reliable and high-performance data processing.
This is an excellent opportunity for a junior data engineer looking to grow within a fast-paced fintech environment while working on modern data technologies.
Team Overview
The Data Management and AI team works across the entire technology stack within QNBeyond Plus.
Our team collaborates with engineering, analytics, and product teams to manage, process, and analyze data that enables innovative digital banking experiences for our customers.
Key Responsibilities
Data Pipeline Development
- Design and build scalable data pipelines for batch and real-time processing.
- Implement ETL/ELT workflows integrating data from APIs, databases, and event streams.
Streaming & Event Processing
- Develop and maintain streaming data pipelines using tools such as Kafka or similar platforms.
- Ensure low-latency, reliable, and fault-tolerant data delivery.
Data Transformation
- Develop data enrichment and transformation workflows to convert raw data into business-ready datasets.
- Implement SQL transformations across layered architectures (raw → bronze → silver → gold).
Data Warehouse Development
- Design and maintain data warehouse models and schemas.
- Optimize query performance and storage design for analytical workloads.
Data Quality & Reliability
- Implement data validation and quality checks.
- Monitor data pipeline performance and ensure reliability.
Collaboration
- Work closely with engineering, analytics, and product teams to deliver production-ready data solutions.
What We Are Looking For
You must be:
- Self-motivated, proactive, and results-driven
- A team player who enjoys collaboration and learning
- A problem solver who approaches challenges analytically
- Customer-oriented, committed to delivering high-quality data solutions
- Detail-oriented, especially regarding data quality and compliance
- Adaptable and eager to grow in a fast-paced fintech environment
Required Qualifications
Education
- Bachelor's degree in Computer Science, Computer Engineering, or related field
Technical Knowledge
- Understanding of computer systems and cloud environments
- Understanding of network protocols and system connectivity
Systems Skills
- Experience using Linux command line tools
- Familiarity with SSH, SFTP, Bash, IP, ports, and networking concepts
Data Engineering Skills
- Experience developing and optimizing ETL/ELT pipelines
- Experience with tools such as Informatica PowerCenter, Kafka, NiFi, or similar
Data & Analytics
- Strong SQL skills
- Understanding of data warehousing concepts and schema design
- Experience with data modeling and data lifecycle management
Programming
- Programming experience using Python
- Scripting experience using Bash or similar tools
Experience
- 2+ years of experience working with ETL or data engineering workflows
- Experience with Informatica PowerCenter and MDM
- Experience developing and scaling data models within modern data warehouse architectures
- Experience implementing data enrichment and transformation logic
- Experience optimizing queries and storage design for analytics workloads
- At least 1 year of experience in fintech, regulated environments, or PCI/DSS compliance is preferred
- Familiarity with performance monitoring tools
