Data Engineer

Join Easygenerator and build the data platform powering the future of learning

Step into an exciting role with an innovative e-learning software company in the EdTech space as a Data Engineer.

Easygenerator is a fast-growing scale-up revolutionizing e-learning with our award-winning authoring tool. Join us to build scalable data solutions that enable smarter decisions across Product, Marketing, Revenue, and Business Intelligence.

What's in it for you?

• Grow Your Career: Take ownership of our modern data platform and work on high-impact projects spanning analytics, AI, and business intelligence.
• International Environment: Join a dynamic, international team (40+ nationalities) in a fast-growing scale-up where your work directly influences business outcomes.
• AI-First Company: We embrace AI in both our product and internal operations. You'll gain hands-on experience with AI-powered analytics and emerging data technologies.
• Learning & Development: Access continuous coaching, learning opportunities, and the freedom to explore new technologies and best practices.
• Hybrid Working Policy: 3 day on-site / 2-day Work from Home (WFH) split.
  
  

• Build and maintain scalable data pipelines and infrastructure using Snowflake, AWS Glue, and modern ETL/ELT frameworks.
• Integrate data from platforms such as Salesforce, Mixpanel, Segment, Customer.io, Intercom, Google Analytics, and LinkedIn Ads.
• Develop reliable data models, warehouses, and data lakes to support reporting and analytics.
• Implement data quality, monitoring, governance, and security best practices.
• Build AI-powered self-service analytics capabilities for business users.
• Partner with Product, Marketing, Revenue Operations, and BI teams to deliver impactful data solutions.
• Optimize platform performance, reliability, and cost efficiency.
  
  

• 5+ years of Data Engineering experience.
• Strong expertise in Snowflake, including architecture, performance optimization, governance, and security.
• Experience with AWS Glue (PySpark), ETL/ELT pipelines, and workflow orchestration.
• Advanced SQL and Python skills.
• Experience with PostgreSQL, MongoDB, Amazon S3, and modern cloud data architectures.
• Strong understanding of data modelling, warehousing, and analytics engineering practices.
• Experience integrating SaaS platforms and customer, product, marketing, or revenue data.
• Knowledge of data governance, privacy, and compliance frameworks such as GDPR.
• Strong problem-solving skills, ownership mindset, and attention to detail.
  
  

• Experience in a B2B SaaS environment.
• Power BI experience, including data modeling and DAX.
• Experience with Snowflake Cortex AI and AI-powered analytics solutions.
• Knowledge of marketing attribution and revenue analytics.
• Experience with Streamlit, Mixpanel, or similar analytics tools.