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.

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.

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