Senior Data Engineer

We are DIGIPAL, a software delivery agency specialising in building high-performing product design and software development teams for clients across Europe and North America. We work with a wide range of organisations from ambitious startups to multinational corporations. We have a unique career opportunity for you to work on building exciting digital products for international clients.

WHO WE ARE LOOKING FOR:

We are looking for a Senior Data Engineer with strong expertise in AWS and modern data engineering practices. You will be responsible for building reliable, scalable data pipelines and working across the AWS ecosystem to support efficient data processing and lifecycle management.

WHAT YOU WILL DO:

• Design, develop, and maintain scalable data pipelines using AWS services.
• Build and manage ETL/ELT and data processing workflows using AWS Glue, DMS, Redshift, and S3.
• Develop production data transformations and Change Data Capture (CDC) processes using Scala.
• Build reliable and maintainable data pipelines using Python and Bash.
• Manage data workflows and lifecycles across the AWS ecosystem.
• Optimize Spark jobs and data processing workloads for performance and scalability.
• Implement robust, idempotent, and fault-tolerant data pipelines.
• Optimize data processing through effective partitioning, columnar storage formats, and distributed processing techniques.
• Monitor pipeline performance, troubleshoot issues, and improve system reliability.
• Collaborate with other engineers and stakeholders to deliver high-quality data solutions.
• Contribute to CI/CD processes and automation for data engineering workflows.

WHAT WE EXPECT FROM YOU:

• 4+ years of commercial experience as a Data Engineer.
• Strong hands-on experience with AWS, particularly Glue, DMS, Redshift, and S3.
• Strong programming experience with Python, Scala, and Bash.
• Experience using Scala for production data transformations and/or CDC workflows.
• Experience using Bash for automation and CI/CD operations.
• Strong understanding of data engineering principles and distributed data processing.
• Experience with Apache Spark and performance optimization.
• Understanding of reliable, idempotent, and fault-tolerant pipeline design.
• Knowledge of partitioning, Parquet/columnar data formats, and Spark optimization techniques such as broadcast joins.
• Ability to work across the AWS ecosystem and manage end-to-end data lifecycles.
• Strong analytical and creative problem-solving skills.
• Excellent attention to detail and passion for building high-quality data solutions.
• Excellent written and spoken English (B2+/C1).

OUR OFFER:

• Remote work setup
• Long term B2B Contract
• Attractive compensation package
• Opportunities for professional growth and development
• Collaborate with top minds from around the globe
• Build world-class digital products for European and US markets