Java Engineer Data Engineering

About SPAN Digital

SPAN Digital is a premium software solution development firm that strategizes, designs, and develops software solutions for clients from startups to global brands. We help engineering teams successfully navigate the challenges caused by the accelerating pace of change in software development, enabling them to build better digital solutions. With headquarters in San Francisco, USA, and development offices in Cape Town, South Africa, and Guadalajara, Mexico, we focus on the entertainment, technology, and medical industries.

We are seeking a Java Engineer with Data Engineering experience to join our expert team focused on executing critical enterprise data processing and pipeline development projects. This role combines developing software engineering skills with hands-on data engineering experience to contribute to production-quality solutions handling large-scale data processing for a client we can t mention, but you’ve definitely heard of!

As an Engineer, you will develop software features and contribute to building quality data processing solutions as part of a collaborative engineering team. You ll apply technical skills to deliver production-ready code while learning from more experienced engineers, taking ownership of well-defined tasks, and demonstrating growing independence in solving technical problems.

Experience Level: 4-7 years in software engineering with foundational data engineering experience

• Implement data processing features within large-scale data migration and transformation pipelines
• Develop and maintain ETL components using Java, or Scala
• Following established patterns and best practices
• Build data validation and testing components to ensure data quality and pipeline reliability
• Contribute to streaming and batch processing solutions using Apache Spark and related technologies
• Support data lineage tracking and monitoring systems under guidance from senior engineers
• Participate in data pipeline testing and debugging to ensure accuracy and performance

• Write clean, maintainable code following team coding standards and best practices
• Participate actively in code reviews both as a reviewer and a reviewee to improve code quality
• Develop comprehensive unit and integration tests for data processing components
• Collaborate on technical design discussions and contribute ideas for solution improvements
• Support deployment and monitoring of data processing systems in production environments
• Document technical solutions and maintain clear technical documentation

• Work effectively within project teams to deliver solutions that provide value to clients
• Seek clarification on requirements to ensure solutions align with client expectations and business objectives
• Communicate progress and blockers clearly to team leads and project stakeholders
• Learn from senior engineers through pair programming, mentorship, and collaborative problem-solving
• Contribute to team retrospectives and process improvement initiatives

• 4-7 years of software engineering experience with foundational technical capabilities
• Bachelor s degree in Software Engineering, or related field (or equivalent experience)
• Demonstrated experience with Java and/or Scala programming languages
• Basic understanding of data engineering concepts and ETL pipelines

• Proficiency in Java or Scala with an understanding of functional programming concepts
• Familiarity with Apache Spark, PySpark or similar big data processing frameworks
• Experience with build tools such as Maven, Gradle, or SBT
• Understanding of SQL and relational database concepts
• Basic knowledge of distributed systems and data processing patterns
• Familiarity with testing frameworks and test-driven development practices

• Experience with Scala or Python for data processing applications
• Familiarity with Hadoop ecosystem including HDFS, Map Reduce, and related tools
• Experience with cloud platforms (AWS, GCP, or Azure) and their data services
• Familiarity with containerization technologies like Docker and…