Data Engineer

Kick-start your career in the online gaming world and experience the very latest in technology and innovation.

We’re part of Super Group, the NYSE-listed digital gaming company behind some of the world’s leading Sports and iGaming brands.

At Digi Outsource, we bring passionate people and innovative tech together to create market-leading online gaming solutions. Our multidisciplinary teams are passionate about products, customer experience and security. We’re empowered to achieve the ultimate in high-performance gaming experiences using the best technology available.

We’re on a thrilling journey of growth and innovation, and we need passionate, driven individuals to join us. At Digi Outsource, every day is action-packed, and we expect you to bring your A-game. In return, you’ll find a supportive environment where your skills can flourish, and your career can soar.

Ready to become a game-changer? Supercharge your career with us and be part of something extraordinary.

We’re on a mission to create extraordinary experiences for our customers, and we believe that your unique skills, passion and superdrive will help us achieve our vision.

As a Data Engineer within our Fintech ecosystem, you'll focus on building and maintaining the data pipelines and processes that power our financial analytics, reporting, and decision-making. You'll work with data from diverse systems—ranging from transactional platforms to customer engagement tools ensuring it is reliable, accessible, and optimized for high-impact use.

This role is essential to support our transition to modern data practices, including cloud-native architectures and real-time processing, while maintaining the continuity and stability of our on-premises operations. Your work will directly enable smarter, faster financial services and help shape the future of data in Payments.

• Developing and maintaining data pipelines to support real-time and batch processing.
• Writing and optimizing SQL queries, stored procedures, and scripts for data processing.
• Supporting ETL/ELT workflows for data integration and transformation.
• Collaborating with team members to integrate data from various sources into centralized systems.
• Implementing and managing data streaming solutions using platforms like Kafka or RabbitMQ.
• Ensuring data quality and reliability across all pipelines and processes.
• Monitoring and troubleshooting data pipelines to ensure performance and reliability.
• Documenting data workflows and providing support for data-related issues.

The necessary skills that we require for this role include:

• Bachelor’s degree in computer science, Data Engineering, Information Systems, or a related field.
• 3-4 years of experience in data engineering or related roles.
• Strong SQL skills, including querying and optimizing database operations.
• Experience developing data pipelines for real-time and batch processing.
• Hands-on experience with data streaming platforms such as Kafka or RabbitMQ.
• Familiarity with ETL processes and tools.
• Proficiency in a programming language such as Python or Java for data tasks.
• Knowledge of data modelling basics for relational databases.
• Attention to detail and a commitment to ensuring data accuracy and reliability.
• Problem-solving skills and the ability to troubleshoot issues in data systems.

It would be great if you also have some of the following skills:

• Relevant certifications (e.g., AWS Certified Data Analytics Specialty, Microsoft Certified: Azure Data Engineer, or Databricks Certified Data Engineer).
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and cloud-based data services.
• Exposure to big data technologies such as Spark or Hadoop.
• Exposure to Apache Spark, Airflow, Kafka
• Knowledge of data governance and compliance standards.
• Experience with data formats like JSON or Parquet.
• Writing clean, modular code for data processing, automation, and integration with APIs or cloud services.
• Basic understanding of containerization tools such as Docker.
• Interest in learning and adopting emerging data technologies.