Senior Data Engineer, Platform.sh

• Strong Python Expertise: Proven experience writing production-grade code in Python, particularly for data ingestion, transformation, and pipeline orchestration
• Advanced SQL Skills: Strong command of SQL for working with large databases, building complex queries, and optimizing for performance in analytical environments
• DBT Proficiency: Hands-on experience using DBT to build, test, and maintain data models that support analytics and business decision-making
• Database Familiarity: Experience with relational databases such as PostgreSQL and MySQL, and a solid understanding of data modeling techniques
• ETL/ELT Pipeline Experience: Experience designing and maintaining ETL/ELT pipelines for large-scale data processing, including querying APIs for data ingestion
• Strong Problem-Solving Skills: Ability to evaluate tradeoffs and design data solutions that are scalable, maintainable, and aligned with business priorities

Desirable

• As a Senior Data Engineer at Platform.sh, you are at the heart of transforming data into strategic insight
• You help make the company smarter while driving innovation, product excellence, and operational clarity by building the data infrastructure that powers our understanding of customer behavior, product usage, and business performance
• In this role, you lead the design and implementation of scalable data pipelines and models, directly supporting decision-making across product, marketing, finance, and customer success
• You apply engineering rigor to turn complex, fragmented data into accessible, trusted assets
• Your architectural thinking and problem-solving skills ensure we scale efficiently while keeping data quality, performance, and usability front and center
• You work in a remote-first environment with a talented, globally distributed team of data and analytics engineers, constantly learning and evolving alongside some of the most interesting minds in data and cloud technology
• Build Data Pipelines: Design and implement robust batch and real-time pipelines using Python and SQL across multi-cloud environments
• Model Data with DBT: Develop and optimize modular, testable DBT models to transform raw event and operational data into business-ready datasets that power reporting and analysis
• Translate Business Needs into Data Solutions: Gather requirements from stakeholders and shape them into well-structured datasets and data products that reflect business logic in a multi-cloud environment
• Solve Complex Data Challenges: Tackle ambiguous data problems with a strong architectural mindset, evaluating tradeoffs and crafting scalable, maintainable solutions
• Collaborate Across Engineering Teams: Align closely with other Platform.sh engineers to ensure consistency in tooling, patterns, and governance across our broader platform

• You can expect 4 interviews on Google Meet to follow the order below. Should you successfully move through the entire process you will have the opportunity to meet with a variety of Platformers. Our goal is to ensure you can make the most informed decision on whether this role, and our culture aligns with what you’re looking for in your future working environment
• 45 Minutes with Talent Acquisition
• 60 Minutes with Hiring Manager (Director, Data Science & Engineering)
• 60 Minutes with Team (ICs, Data Engineer, Data Analytics Engineer)
• 45 Minutes with Executive (CFO)