Data Engineer

Job description

**ABOUT BURGA** From a 7m² flat with just one printer in 2015 to a global powerhouse with 4+ million customers, 12+ million products sold, and revenue of over $147 million in 2025, BURGA is not your average brand. Our products have been spotted with some of the world’s biggest celebrities, like Taylor Swift, Cara Delevingne, Lucy Hale, Alexis Ren, and many more. We’re on a mission to turn ordinary into extraordinary by transforming everyday items into style statement accessories. We’re scaling fast, thinking big, and bringing that vision to life at our €10 million manufacturing facility in Kaunas, capable of producing 40,000 items a day. With unicorn ambitions and 500+ passionate humans on a mission to conquer the world, you’re joining a team that’s rewriting the rules. Oh, and we just landed a spot among Lithuania's TOP 10 most attractive employers in 2026, so the word is officially out. Curious about our day-to-day life? Take a peek at Instagram [@burgainsider](https://www.instagram.com/burgainsider/?hl=en) **ABOUT THE POSITION****Data Engineer** at is a key role in building and scaling the foundation of our modern data platform. You’ll take ownership of the entire data ingestion layer — ensuring that data from 100+ business systems is reliably replicated, monitored, and available for analytics and decision-making across the company. *Your Role:* You’ll design, develop, and operate scalable data ingestion pipelines, build custom connectors, ensure reliability and observability across the platform, and collaborate closely with Data Modeling and Analytics teams to provide high-quality, trustworthy data for downstream use cases. **WHAT YOU’LL DO** - Build, maintain, and optimize data ingestion pipelines connecting 100+ source systems to BigQuery - Develop custom connectors using Python and other data languages for unsupported or complex data sources - Design and maintain DAGs for orchestration, dependency management, and retry logic - Monitor data pipelines and proactively identify issues related to freshness, schema drift, failures, or data quality - Implement alerting, observability, and operational processes for the ingestion layer - Collaborate with Data Modeling and Analytics teams to align on data contracts, schema expectations, and source reliability - Manage API integrations across REST, GraphQL, and webhook-based services - Contribute to CI/CD workflows, automated testing, and deployment processes for connectors and pipelines - Document integrations, operational runbooks, and ingestion architecture standards - Support onboarding of new business data sources and help scale the overall data platform infrastructure **WHAT WE’RE LOOKING FOR** - 2–3 years of experience in Data Engineering, DataOps, Platform Engineering, or similar roles - Strong Python skills for data pipeline and connector development - Solid SQL knowledge and understanding of cloud data warehousing concepts (preferably BigQuery) - Hands-on experience with ETL/ELT pipelines, or data ingestion frameworks - Experience with workflow orchestration tools such as Airflow, Prefect, or Dagster - Familiarity with Docker, Kubernetes, and cloud environments such as GCP, AWS or Azure - Experience integrating third-party APIs (REST, GraphQL, OAuth2, webhooks, etc.) - Understanding of monitoring, alerting, and operational ownership in production data environments - Experience with Git/GitHub, CI/CD pipelines, and code review practices - Strong ownership mindset and ability to independently troubleshoot and resolve technical issues - Excellent communication and collaboration skills when working across technical and business teams **SALARY:** 3800 - 5000 Eur/month GROSS