About Moonlit
Moonlit is a legal publisher serving tens of thousands of legal professionals globally through its platform, API, and MCP server. It maintains Europe's largest legal database, enriched and structured to power semantic search, AI assistants, and legal AI products.
Responsibilities
•Build and optimize ETL pipelines using Python, PySpark, and Databricks
•Add legal data sources by scraping, parsing, and normalizing documents in formats such as HTML, XML, and PDF
•Enrich and structure datasets, including metadata, document references, and legislation versioning
•Maintain and optimize Elasticsearch indexes for fast, reliable search
•Monitor data quality, freshness, and source coverage
•Improve pipeline performance, reliability, and cost
•Manage data infrastructure on Azure
•Collaborate with platform developers, AI engineers, legal experts, and business stakeholders
•Own end-to-end data workflows, from source data to searchable, enriched documents
•Build tested, monitored, and scalable production systems
•Serve as the go-to person for data structure and provenance
Requirements
•1–3 years of experience in data engineering or a related field
•Strong Python skills and experience with PySpark and large-scale data processing
•Solid SQL skills and understanding of data modeling
•Hands-on experience with at least one major cloud platform: Azure, AWS, or GCP
•Experience building ETL pipelines and data transformation workflows
•Comfortable working with messy, unstructured data
•Pragmatic mindset, choosing robust solutions over clever ones
Nice to have
•Experience with Databricks and/or Elasticsearch
Conditions
•Competitive salary with equity package
•Office with a large garden
•International, mission-driven work environment
