Data Engineer at DigiOutsource

Why we need you

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.

What you’ll be doing

• 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.

Essential skills you’ll bring to the table

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.

Desirable skills you’ve got up your sleeve

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.