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