Senior Data Engineer

Appliscale is an independent Technology Consultancy specializing in bespoke, cloud-based systems and full-cycle engineering - from business analysis to architecture design, development, and deployment. They work across industries including gaming, proptech, legaltech, and adtech, partnering with startups, scaleups, and Fortune 500 companies worldwide. Their current focus is on building intelligent agents for automation and scalable agentic ecosystems. The company has a flat structure, remote-first culture, and self-organized teams.

• Minimum of 5 years commercial experience in data engineering or related field
• Bachelor’s or higher degree in Computer Science, Software Engineering, or related field
• Proficiency in Python for data processing and analysis
• Hands-on experience with DBT (Data Build Tool) and Airflow
• Commercial experience with PySpark and Databricks
• Proficiency in AWS cloud infrastructure
• Effective communication and teamwork skills

Nice to have:

• Experience with ML Operations and GenAI pipelines and infrastructure
• Experience in the gaming industry, particularly with online multiplayer games
• Experience working with cross-discipline organizations building data products
• Proficiency in large-scale data manipulation across various data types
• Ability to troubleshoot and optimize complex ETL pipelines
• Proven experience mentoring and guiding other engineers

• Design, build, and optimize scalable pipelines supporting the Data Foundation ecosystem
• Design and implement data models capturing internal customer experiences with accuracy and scalability
• Architect and implement robust, maintainable, and high-performance data solutions
• Automate workflows to enhance data processing efficiency for content, growth, and pubsports areas
• Optimize query performance and resolve pipeline bottlenecks
• Evaluate and adopt new tools and methodologies to advance data engineering capabilities
• Support cost optimization by ensuring scalable and efficient data solutions
• Ensure data quality, governance, and compliance with regulatory standards such as GDPR and CCPA
• Contribute to engineering discipline by shaping infrastructure, standards, tooling, and best practices