Analytics Engineer
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At Lexroom.ai , we set the bar for legal AI—clear, fast, and built for trust. In just a few years, what began as an idea has become a reliable platform adopted by thousands of legal professionals across Europe . Our mission is clear: make the law faster, clearer, and more reliable , giving lawyers, law firms, and companies the time and confidence to focus on what truly matters. We’re scaling rapidly, backed by top-tier investors and a world-class team dedicated to rigor, clarity, and impact. Today, Lexroom is a trusted partner , shaping the future of legal AI with discipline and purpose. Why Lexroom.ai ?
- Shape the Standard: Be part of the team setting the benchmark for legal AI in Europe.
- Work with the Best: Collaborate with exceptional colleagues in a culture that values competence, curiosity, and ambition.
- Deliver Meaningful Results: Your work will directly influence how legal professionals operate—faster, clearer, and more efficiently.
- Own the data transformation layer from raw sources to trusted, documented datasets—designing and maintaining a dbt project on BigQuery with staging, intermediate, and mart layers.
- Model product analytics events (user interactions, feature adoption, feedback signals), engineering metrics, and business KPIs into reliable, self-service data models.
- Build and maintain the data foundations powering our dashboards, decisions, and team health metrics.
- Implement data quality frameworks: tests, freshness checks, anomaly detection, and clear ownership and SLAs on key datasets.
- Collaborate with engineers to improve event tracking and data contracts at the source (Pub/Sub, application events).
- Create and curate dashboards and semantic layers that Product, CS, and Sales teams can query directly—enabling true self-service analytics.
- Partner with the AI & Search Platform team to instrument and measure model performance, feedback loops, and benchmark results.
- Support Product teams with ad-hoc analysis: feature impact, user segmentation, satisfaction trends, and power-user behavior.
- 3+ years of experience in analytics engineering, data engineering, or a data analyst role with a strong engineering mindset.
- Expert SQL skills and hands-on experience with dbt (dbt Core or dbt Cloud).
- Solid experience with BigQuery or comparable cloud data warehouses (Snowflake, Redshift).
- Strong understanding of dimensional modeling, data testing, and documentation-as-code practices.
- Comfortable working in a Python ecosystem (scripting, basic ETL, notebooks for exploration).
- Experience building data models that serve multiple stakeholders (product, engineering, business).
- Fluent English; Italian is a strong plus.
- Experience with event-driven architectures (Pub/Sub, Kafka) and streaming data.
- Familiarity with Elasticsearch, Pinecone, or vector databases.
- Exposure to engineering metrics (DORA, PR analytics) or developer productivity measurement.
- Experience with BI/visualization tools (Retool, Looker Studio, Metabase).
- Interest in AI/ML model evaluation and LLM output quality measurement.
- Previous experience in legal-tech, RegTech, or B2B SaaS.
- Annual Salary Range: €45,000 – €70,000
- Equity Package: Align your growth with the company’