• You will own and evolve our data pipelines on GCP — building new ones, hardening existing ones, improving data quality, and making clean, trustworthy data available across the organisation. • Designing ELT/ETL processes on BigQuery and ClickHouse, building real-time pipelines on Pub/Sub and Kafka with Dataflow (and where it fits, Flink/Spark). • Orchestrating workflows with Airflow, and ensuring data is properly cleaned, modelled, and served for analytics, ML training, and online inference. • Partnering with ML engineers on feature pipelines, monitoring data drift, and keeping models well-fed and retrained as needed. • Consuming and building REST APIs, integrate with third-party SaaS sources, and treating infrastructure as code. • Collaborating closely with Infrastructure, Software Engineering, Product, and ML/AI engineers. • Helping drive the migration off Snowflake onto GCP-native stack — and retire shadow pipelines along the way. • Owning the orchestration layer in Airflow, including SLAs, retries, and data quality gates. • Modeling data for analytics and for ML — including feature pipelines that serve both training and low-latency online inference. • Capturing requirements from stakeholders and translating them into pragmatic, well-scoped data products. • Continuously improving data quality, reliability, observability, and cost efficiency. • Identifying new data sources worth acquiring and integrating them cleanly.

Role Description Estamos em busca de um Engenheiro de Dados Sênior qualificado e proativo para se juntar à nossa equipe de Desenvolvimento. Se você é um profissional apaixonado por programação gostaríamos de conhecê-lo. - Atuar junto às áreas de negócio para entender necessidades e traduzir requisitos em soluções de dados escaláveis e alinhadas aos objetivos da organização. - Conduzir levantamentos de requisitos e mapear processos de negócio e fluxos de dados entre sistemas. - Definir e validar regras de negócio, métricas, KPIs e indicadores corporativos. - Projetar e evoluir modelos de dados para ambientes de Data Warehouse, Data Lake e Lakehouse. - Definir estratégias de modelagem dimensional, incluindo fatos, dimensões, granularidade e relacionamentos. - Elaborar arquiteturas de dados utilizando Azure Data Factory, Databricks, Data Lake e Power BI. - Garantir a qualidade, consistência e rastreabilidade dos dados ao longo dos pipelines. - Definir padrões para ingestão, transformação, qualidade e disponibilização de dados nas camadas Bronze, Silver e Gold. - Atuar como referência técnica para os times de Engenharia de Dados, BI e Analytics. - Apoiar a implementação das soluções, assegurando aderência às definições de arquitetura e negócio. - Produzir documentação das modelagens, regras de negócio e indicadores corporativos. Qualifications - Experiência sólida em modelagem de dados para ambientes analíticos (Data Warehouse, Data Lake ou Lakehouse), incluindo modelagem dimensional, definição de fatos, dimensões, métricas, indicadores e granularidade. - Vivência em levantamento e tradução de requisitos de negócio para soluções de dados, atuando na definição e padronização de métricas e indicadores corporativos. - Experiência em projetos de arquitetura de dados, integração entre diferentes fontes de informação e governança, qualidade e rastreabilidade de dados. - Capacidade de atuar de forma consultiva junto às áreas de negócio e times técnicos. - Conhecimentos em SQL Avançado, Data Warehouse e/ou Lakehouse, Azure Data Factory (ADF), Databricks, Azure Data Lake Storage, Power BI, Modelagem Semântica e Arquitetura Medallion (Bronze, Silver e Gold). Requirements - Experiência com Microsoft Fabric. - Conhecimento em Data Vault. - Experiência com definição de Single Source of Truth (SSOT). - Conhecimento em Master Data Management (MDM). - Vivência com ferramentas de catálogo e governança de dados. - Experiência em projetos de modernização de Data Warehouse para Lakehouse. - Certificação Microsoft Azure Data Engineer Associate ou correlatas. Benefits - Atuação remota – Segunda a sexta, (09h às 18h); - VR/VA – Valor de R$300,00 por mês cumulativos para gastar como, quando e onde quiser (o valor é creditado na sua conta do Ifood mensalmente e temos o cartão bandeira ELO). - Aniversário – Uma data tão especial, a Rox te presenteia com um vale presente e um Day off para que você possa curtir seu dia; - Blog – Na Rox incentivamos o compartilhamento, caso queira publicar um artigo em nosso blog (a cada 2 posts aprovados) você ganha um bônus; - Cursos – Acesso completo pela RoxSchool, Plataforma Alura, Pluralsight, Oreilly para livros e palestras e RoxSchool; - Certificações – Reembolso de certificação de até R$300,00 (TECNOLOGIA) + Bônus de R$300,00 por certificação alcançada dessas Brands; - Auxílio Psicólogo – Duas sessões de Psicoteparia custeados pela ROX mensalmente com psicólogos parceiros; - WellHub (Gympass); - Oferecemos o equipamento de trabalho.

Role Description Join BILL as a Staff Data Warehouse Engineer and help build the trusted data backbone that powers decision-making across Finance, Product, and Go-to-Market. You’ll be a senior technical owner on our Data Operations & Enablement team, designing and delivering end-to-end pipelines and warehouse architecture that become the single source of truth for the business. If you take pride in building reliable systems the right way, and you enjoy turning ambiguity into well-modeled, performant data products, this is the role to do your career-defining work. In this role, you’ll architect and harden core data infrastructure from ingestion through curated marts that executive leadership and Finance rely on for reporting, planning, and strategic decisions. You’ll partner closely with analytics, data science, and product teams to make integrations robust, patterns reusable, and datasets trustworthy. Bring a builder’s mindset, a bias for simplicity, and a passion for elevating standards. Your work will be the foundation others build on. Responsibilities: - Own end-to-end delivery of pipelines and warehouse architecture, from design through production, for new builds, migrations, and re-platforming efforts. - Administer and harden the data warehouse, including schema design, performance tuning, stability, and cost-aware optimization. - Embed data quality and governance into pipelines by default — testing, documentation, lineage — not as afterthoughts. - Translate ambiguous business requirements into clear technical designs; scope tradeoffs and dependencies with cross-functional stakeholders. - Define and codify simple, stable, repeatable engineering standards and patterns adopted by the broader team. - Mentor engineers through design reviews, code reviews, and hands-on guidance to raise the technical bar. - Evaluate and introduce tools or architecture patterns when they materially improve scale, reliability, or cost and be able to justify and explain the rationale. - Design the warehouse to be queried by AI agents, not just people. Qualifications - 8+ years of experience in data engineering or combined software/data engineering roles, with a track record of owning significant warehouse builds end-to-end. - Expert-level SQL (multiple dialects) and strong Python, with examples of production-grade applications beyond ad hoc scripts. - Deep knowledge of ETL/ELT design, ingestion methods, and orchestration (e.g., dbt, Airflow or equivalents). - Hands-on experience with modern lakehouse/warehouse platforms (e.g. Snowflake, Trino/Starburst, or similar) and understanding of engine tradeoffs. - Experience in financial services and/or SaaS environments. - Comfort operating with minimal DevOps/IT support on core database and warehouse administration. - Proven mentorship and standards-setting experience; formal management not required. Requirements - Visa Sponsorship: This position is not eligible for visa sponsorship. Applicants must have authorization to work in the United States without requiring visa sponsorship now or in the future. Benefits - 100% paid employee health, dental, and vision plans (choose HMO, PPO, or HDHP). - HSA & FSA accounts. - Life Insurance, Long & Short-term disability coverage. - Employee Assistance Program (EAP). - 11+ Observed holidays and wellness days and flexible time off. - Employee Stock Purchase Program with employee discounts. - Wellness & Fitness initiatives. - Employee recognition and referral programs. - And much more.

Role Description Tripadvisor is looking for a Data Engineer II to join our fast-moving Data Platform group. In this role, you will design, build, and sustain the data infrastructure that powers the world’s most trusted travel platform. You’ll bring both strong software engineering fundamentals and hands-on data engineering expertise — writing production-quality Java and Python, architecting reliable pipelines, and delivering end-to-end solutions that scale to hundreds of millions of travelers. Do you enjoy building features end-to-end? Do you thrive working with a broad technology stack, releasing frequently, and collaborating with talented engineers worldwide? If so, we’d love to talk. What You’ll Do - Data Engineering & Data Products, ETLs: - Design, build, and maintain robust ETL/ELT data pipelines that process terabyte-scale data across Snowflake, BigQuery, Hive, and other platforms. - Develop scalable, reusable data models and curated data sets for analytics, data science, CRM, machine learning, and other data consumers across the organization. - Own the full lifecycle of data pipelines: define SLAs, implement performance measurements, monitoring, and anomaly detection. - Ensure enterprise data integrity, validation, documentation, and governance. - Platform & Software Engineering: - Write production Java and Python code across our evolving platform stack — from data ingestion and event processing to REST services and internal tooling. - Build and maintain streaming and batch processing systems (Flink, Spark, Kafka) that power real-time and analytical workloads. - Take responsibility for all aspects of software engineering: design, implementation, QA, and maintenance, with a CI/CD mindset (most engineers release to production every few days). - Operate on and improve cloud infrastructure on AWS, with familiarity with Gradle, Linux, and related tooling. - Quality, Collaboration & Ownership: - Take on projects with independence and a mandate to leave things better than you found them. - Be integral to code quality on your team through leadership in design and code review. - Collaborate closely with Product, Design, Analytics, and Data Science teams to define specifications and deliver high-quality solutions. - Communicate effectively with both technical and business stakeholders; translate complex data problems into clear solutions. - Work alongside engineering groups located around the world in a fast-paced, dynamic environment. Qualifications - 4–5+ years of data engineering or general software development experience in a commercial setting. - Strong hands-on proficiency in both Java and Python for production systems. - Demonstrated experience designing and implementing complex ETL/ELT processes from concept to production. - Proficiency in SQL and data exploration across large, complex datasets. - Experience with big data technologies (Hadoop, Hive, BigQuery, Snowflake) and working with terabyte-scale or larger datasets. - Solid foundation in data structures, algorithms, and object-oriented design. - Professional experience building REST services and working with event queue systems. - Familiarity with Linux and cloud infrastructure design on AWS or equivalent cloud providers. - Systems performance and tuning experience, with an understanding of how architecture impacts scalability. - Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience. - Strong analytical skills; desire to write clean, correct, and efficient code. - Self-paced, organized, and detail-oriented with a strong sense of ownership, urgency, and pride in your work. - Ability to break down complex problems into simple, pragmatic solutions. - Strong interpersonal skills, intense curiosity, and enthusiasm for solving difficult problems. - Willingness and ability to take on new technologies as our stack evolves. Nice to Have - Experience with stream processing frameworks such as Flink or Spark Streaming. - Experience with task orchestration tools such as Apache Airflow or similar systems. - Familiarity with additional technologies: GraphQL, React, HTML5, JavaScript, CSS, Postgres, Gradle, BERT. - Experience working with and designing infrastructures for large-scale data processing (Hive, Snowflake, NoSQL databases). - Experience with data governance practices and tooling. - Exposure to and/or interest in machine learning, data science, or GenAI to help solve engineering challenges innovatively. - Experience developing scalable code for high-volume, low-latency systems. Benefits - We strive to create an accessible and inclusive experience for all candidates. - If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at greenhouse@tripadvisor.com.