Analytics Engineer
Lawhive is an online platform for consumers and small businesses to get legal help for a fraction of the cost of a law firm. Our platform combines regulated human lawyers collaborating alongside the world's first AI lawyer, specifically built for consumer legal work. Equal access to the law is one of the biggest and most pressing unsolved problems in society today. We're passionate about levelling the playing field and believe access to the law should be a basic utility in society. Our AI lawyer Lawrence is built on top of our own fine tuned LLM and recently passed the UK's bar exam equivalent. We're backed by some of the top US and UK VC funds, including Google Ventures, Balderton Capital and TQ Ventures. We recently secured a $40M Series A funding round to facilitate international expansion and to grow our team, representing one of the five largest Series A rounds in Europe for 2024. What You'll Do
- Design, build, and maintain scalable and reliable data models in dbt that serve as the backbone for all company-wide analytics and business intelligence.
- Establish and govern the dbt semantic layer as the single source of truth for all key business metrics, empowering stakeholders to confidently explore data through self-service data products.
- Partner directly with business stakeholders to understand their challenges, translate complex questions into technical requirements, and conduct analyses to uncover actionable insights.
- Lead the architecture and development of our self-service analytics platform using Hex, creating a trusted environment for business users to make data-driven decisions.
- Own the end-to-end testing framework for our dbt models to guarantee data quality, accuracy, and reliability across the entire data platform.
- Proactively optimise our dbt models and BigQuery usage to improve query performance and manage costs, ensuring the long-term scalability and financial efficiency of our data platform.
- Champion and maintain comprehensive documentation for our data models, metrics, and processes to enhance data literacy and discoverability across the organisation. About You
- You have 3-5+ years of experience in analytics engineering, data engineering, or a highly technical data analytics role.
- You have a quantitative background in mathematics, statistics or similar field.
- You think of data models as products, with a passion for building clean, reliable, and intuitive datasets that empower your colleagues.
- Expert-level proficiency in SQL and proven expertise in dbt for developing complex data models, writing custom macros, and implementing robust data quality tests.
- Deep, hands-on experience with a cloud data warehouse like Google BigQuery, including performance tuning and cost optimisation.
- You excel at translating ambiguous business requirements into well-structured, performant, and easy-to-understand data transformations.
- An excellent communicator and collaborator, you are adept at working with both technical (Engineering, AI) and business stakeholders to clarify requirements and drive projects forward.
- Pragmatic and impact-focused, you know how to balance technical debt with shipping value, and can effectively decide when to iterate and when to refactor.
- Highly proactive and autonomous, you thrive in a fast-paced environment and take ownership of your work from ideation to delivery. Bonus points
- Experience helping to build a company's data analytics function from an early stage.
- Programming experience with Python for data automation or analysis.
- Proficient with GitHub for version control and collaboration
- Direct experience working with our specific stack: BigQuery, dbt, and Hex.
- Background in a consumer marketplace or another fast-growth startup.
- Working knowledge of infrastructure-as-code tools like Terraform.
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