• Desenvolver, manter e otimizar pipelines de dados escaláveis; • Trabalhar com processamento distribuído utilizando Apache Spark; • Orquestrar workflows e rotinas de dados com Apache Airflow; • Desenvolver soluções em Python seguindo boas práticas de engenharia; • Atuar em ambientes cloud, especialmente Microsoft Azure; • Criar e manter pipelines de deploy utilizando práticas de CI/CD; • Trabalhar com arquivos de configuração e automação em YAML/YML; • Utilizar Docker para conteinerização de aplicações e serviços; • Desenvolver, testar e documentar modelos de transformação de dados com dbt; • Colaborar com times de engenharia, analytics e negócio para garantir qualidade, confiabilidade e performance das soluções; • Apoiar decisões técnicas relacionadas à arquitetura, performance, observabilidade e governança de dados.

About Eve Eve is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, recover more for clients, and grow with AI that works across every stage of a case, from intake through resolution. The next generation of great plaintiff firms will be AI-Native, and Eve is how they get there. But what makes Eve different isn't just the product. It's how we build it. If you're someone who takes ownership, stays curious, and wants to build AI that's already changing how law is practiced, this is where you belong. Product-market fit: Eve is trusted by over 1000+ law firms, and we’re growing fast. Backed by top investors: We’ve raised over $160M from world-class partners including Spark Capital, Andreessen Horowitz(A16z), Menlo Ventures, and Lightspeed. Built by a world-class team: Engineers, designers, and operators from places like Scale, Meta, Airbnb, Cruise, Square, Rubrik, and Lyft are building Eve from the ground up. AI-Native from day one: We’re on the bleeding edge of AI, collaborating directly with teams at OpenAI and Anthropic to build best-in-class AI workflows tailored for legal work. Explosive growth: We are growing 2X revenue Quarter over Quarter. What You'll Do: - Design and build Eve’s data warehouse architecture from the ground up, including schema design, data modeling, and pipeline orchestration. - Develop and maintain reliable ETL/ELT pipelines that integrate data across core business systems (CRM, product, billing, marketing, etc.). - Define and implement core business data models that standardize how Eve measures pipeline, conversion, revenue, customer health, and attribution. - Build a reliable GTM data layer that enables marketing, sales, CS, and finance teams to self-serve key insights without ad hoc analysis. - Establish data quality, governance, and monitoring practices to ensure accuracy and reliability across the data stack. - Create cross-functional intake and prioritization processes for data requests, balancing infrastructure work with business needs. - Partner closely with GTM, finance, product, and engineering teams to understand their workflows and translate them into durable data systems. - Select and manage Eve’s data stack (warehouse, orchestration, transformation, BI tooling). - Lay the foundation for product analytics and behavioral event tracking across Eve’s platform. - Build and scale Eve’s data function over time, including hiring, team structure, and operating processes. What We're Looking For: - Proven experience building a data warehouse and core data infrastructure from scratch at a high-growth SaaS or technology company. - Deep expertise in data engineering, including data modeling, ETL/ELT pipeline design, and warehouse architecture. - Strong proficiency with SQL and modern data stack tools (e.g., Snowflake/BigQuery/Redshift, dbt, Airflow/Prefect, etc.). - Experience integrating and modeling data from GTM systems such as CRM, marketing automation, billing, and customer success platforms. - Demonstrated ability to translate business workflows into durable data models that teams can rely on for decision-making. - Comfortable operating in early-stage environments with messy, incomplete, or inconsistent data. - Strong cross-functional communication skills and ability to work closely with sales, marketing, CS, finance, and product teams. - Experience owning architectural decisions for the data stack, including tooling selection and infrastructure design. - Familiarity with product analytics and event instrumentation across web or application platforms. - Fluency with AI-assisted development tools such as Cursor, Claude Code, or GitHub Copilot. - Entrepreneurial mindset with a desire to build and own a data function from the ground up. Final compensation will be determined based on a variety of factors, including but not limited to relevant experience, skills, interview performance, and the scope and level of the role and candidate. US Base Salary Range $280,000—$350,000 USD Benefits 💰 Competitive Salary & Equity 💹 401(k) Program with Employer Matching ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚗 Commuter Benefits* 🧑‍💻 Autonomous Work Environment 🖥️ Workplace Setup Reimbursement 🏠 Telecomm Stipend 🏝 Flexible Time Off (FTO) + Holidays 🚀 Quarterly Team Gatherings 🥪 In office Perks* *In office employees only Eve Legal is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation during the application process, reach out to your recruiter. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

• Drive the design, development, and operationalization of advanced large-language-model capabilities across a cloud-based analytics ecosystem. • Lead innovation efforts around cutting-edge AI, owning the architecture and strategy for fine-tuning and Retrieval-Augmented Generation (RAG). • Guide the development of high-impact prototypes and oversee the evolution of scalable LLM pipelines. • Ensure robust governance, security, and performance across all model implementations. • Provide technical leadership, evaluate emerging LLM technologies, set best practices, and help drive transformation through effective deployment of generative AI.

• Connect to client systems — databases, APIs, CRMs, and other SaaS tools — and get data reliably out of and into them. • Extract, clean, transform, and move data so it is structured and usable by AI features, including retrieval and agentic workflows. • Build and maintain data pipelines that feed the Applied AI Engineer’s RAG and agent systems with current, correct data. • Use AI coding tools to accelerate integration work, while applying real engineering judgment to the bespoke, messy parts those tools handle poorly. • Handle the practical realities of client data: undocumented schemas, inconsistent formats, partial records, and access constraints. • Apply data-handling, security, and privacy best practices throughout, especially with client data. • Collaborate with the Builder and the Applied AI Engineer to ensure data flows cleanly end to end, and document integrations and pipelines in Notion so they are repeatable and maintainable.