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Data Platform/Infrastructure EngineerLovable · Stockholm
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Lovable

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Data Platform/Infrastructure Engineer

🗓️ Posted 2025-08-22 Stockholm Fulltime Hybrid ICT
💰 Salary Not shared 📊 Market 45,000 SEK–65,000 SEK/mo

Responsibilities

  • ● TL;DR - We are looking for data engineers to design, build, and maintain the end-to-end declarative data platform that powers ingestion, transformation, and consumption across Lovable. You are obsessed about empowering teams to ensure data systems are scalable, reliable, safe and easy to use.
  • ● WHY LOVABLE
  • ● Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we're just getting started.
  • ● Lovable is one of TIME's 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe's fastest-growing AI companies and one of the most ambitious places to build in this next era of software.
  • ● WHAT WE ARE LOOKING FOR:
  • ● Strong experience with cloud-based data platforms (Snowflake, BigQuery, Redshift, Databricks or similar).
  • ● Deep understanding of data ingestion frameworks, orchestration(Airflow, Dagster, Prefect or similar) and infrastructure as code (Terraform, Pulumi or similar).
  • ● Familiarity with event-driven architectures (Kafka, Pub/Sub, Kinesis or similar).
  • ● Proficiency in SQL, and distributed systems. Knowledge in Go is a plus.
  • ● Strong communication and documentation skills. Be able to align technical details with strategic goals.
  • ● WHAT YOU WILL DO:
  • ● Develop and maintain core data infrastructure (data lake, warehouse, orchestration, observability, governance).
  • ● Partner with other platform and domain teams to design data pipelines and implement declarative configuration for ingestion and transformation.
  • ● Ensure data quality, lineage, and security standards are embedded across all workflows.
  • ● Collaborate with Analytics Engineers to define modeling conventions and enforce schema governance.
  • ● Implement CI/CD pipelines for data systems and assist with cost optimization and performance tuning.
  • ● Define data platform best practices and support self-service enablement.
  • ● OUR TECH STACK