Nosso Modo de Fazer no Time: Transforme sua carreira com o iFood! Somos uma empresa brasileira de tecnologia referência na América Latina. Por meio de soluções inovadoras, conectamos milhares de restaurantes a milhões de consumidores diariamente com uma média de 100 milhões de pedidos mensais. Além do delivery de comida, também somos Mercado, Farmácia e Pet. Temos também o iFood Pago, nossa Fintech, que engloba o iFood Benefícios, o vale alimentação e refeição do iFood e o próprio iFood Pago, o banco do restaurante. Junte-se a nós e faça parte de uma equipe que está sempre à frente com tecnologia de ponta e inovação constante. Você fará parte do time de Governança de Dados, com o desafio de melhorar a descoberta de dados, assim como toda a camada de metadados e ciclo de vida dos dados que temos, definindo e construindo o modo de trabalhar com dados aqui dentro, colaborando ativamente com times de engenharia, arquitetura e dados para garantir que tenhamos dados confiáveis, documentados, seguros e acessíveis. Esta é uma posição com componente técnico em desenvolvimento e foco em identificar oportunidades e aplicar boas práticas de governança em ambientes modernos de dados em nuvem. Seu Cardápio Diário: - Definirá políticas e processos de governança de dados (catalogação, linhagem, entre outros); - Ajudará a projetar e construir soluções que facilitem a aderência às políticas definidas; - Participará da definição e evolução do framework de governança, promovendo a cultura de dados entre os times; - Apoiará iniciativas de novas tecnologias e modos de trabalhar com dados para garantir que surjam com governança definida, ajudando domínios de dados a adotarem práticas de ownership e interoperabilidade; - Irá desenvolver monitores e indicadores de governança; - Colaborará com arquitetos e engenheiros para garantir que os pipelines de dados estejam em conformidade com as políticas definidas; - Traduzirá requisitos de governança em soluções técnicas alinhadas às boas práticas de engenharia e realidade do negócio. Ingredientes Que Buscamos: - Experiência prévia com governança de dados (Data Governance, Data Stewardship, Data Quality, Metadata Management etc.); - Capacidade de adequar a teoria de governança para a realidade da operação do dia a dia; - Experiência em engenharia de dados ou software (construção de pipelines de dados, micro serviços, git, testes, modularização e orquestração); - Sólido entendimento do ciclo de vida de dados e de princípios de arquitetura moderna (Data Lake, Lake house, Data Warehouse); - Conhecimento em cloud (AWS, GCP ou Azure); - Capacidade de escrever e interpretar queries em SQL e scripts em Python para análise, transformação e validação de dados; - Boa comunicação com públicos técnicos e não técnicos; habilidade de traduzir complexidade técnica em linguagem acessível; - Experiência com gestão de metadados, linhagem de dados, catalogação e classificação - Mindset colaborativo, resiliente e voltado à melhoria contínua; Para realçar o sabor: - Conhecimento ou certificações em frameworks de governança de dados (ex: DAMA-DMBOK, DCAM, EDM Council); - Experiência com ferramentas de monitoramento e visualização de dados; - Experiência com ferramentas de catálogo como DataHub e OpenMetadata; - Conhecimento em Data Warehouse, Bancos de dados e Kafka; - Conhecimentos de ferramentas como Airflow, Spark, Databricks, DBT ou similares; Buscamos uma pessoa apaixonada por inovação e tecnologia, que esteja sempre em busca de novos aprendizados e que goste de desafios. Se você se identifica com este perfil, adoraríamos conhecer você!

• Support the Bank’s “People First” focus and rules of engagement—maintaining a professional demeanor, working as an active member of the CNOB team, providing clients excellent service, always striving to make CNOB “A Better Place to Be” • Architect, build, and maintain data pipelines using Apache Airflow, ensuring seamless data movement across AWS S3 and Amazon Redshift. • Design and implement scalable data models using dbt Labs, transforming raw data into clean datasets optimized for analytical querying. • Facilitate the setup of new data sources, designing the architecture to securely and efficiently ingest data from third-party APIs, transactional databases, and external platforms into the data lake/warehouse. • Maintain a deep understanding of the underlying data model to troubleshoot bottlenecks, optimize Redshift query performance, and implement rigorous data quality testing and alerting. • Serve as a subject matter expert on data architecture, establishing best practices for code reviews, version control, and CI/CD workflows within the data engineering team.

Role Description We’re hiring a Staff Data Engineer to design and build robust data pipelines for our corporate Data Lake. In this role, you’ll own data products end-to-end in production, work autonomously on significant projects, and mentor junior engineers. You’ll be expected to make sound data engineering trade-offs under limited supervision, with strong hands-on experience in Spark, Databricks, Delta Lake, and Airflow. At Pismo, the Data Lake team is responsible for centralizing and organizing data into a single, trusted platform that supports decision-making across the company and for external clients. We work on challenges such as: - Scaling global data infrastructure - Delivering high-quality reporting - Enabling secure, self-service access to data Key responsibilities include: - Design and implement data ingestion and transformation pipelines (batch and near-real-time) using PySpark/SparkSQL on Databricks. - Own data pipelines end-to-end in production: freshness, correctness, availability, and SLA adherence. - Build and maintain Delta Lake tables following medallion architecture patterns (bronze/silver/gold). - Design and optimize Airflow DAGs (MWAA) for complex orchestration scenarios. - Implement and maintain data quality frameworks (Great Expectations or equivalent) as integrated pipeline gates. - Write advanced SQL for data modeling, transformation, and performance optimization. - Conduct thorough code reviews and mentor Analyst-level engineers through pairing and design guidance. - Investigate, diagnose, and resolve data quality incidents and pipeline failures independently. - Collaborate with Analytics, BI, and Product teams to design consumer-friendly datasets. - Contribute to CI/CD, testing standards, and data governance practices. This is a remote position. A remote position does not require job duties to be performed within proximity of a Visa office location. Remote positions may be required to be present at a Visa office with scheduled notice. #LI-Remote Qualifications - Apache Spark (PySpark, SparkSQL) — production experience - Databricks (jobs, workflows, cluster management, tuning) - Delta Lake (ACID tables, OPTIMIZE, VACUUM, schema evolution, MERGE) - Advanced SQL (window functions, CTEs, query optimization) - Apache Airflow / MWAA (DAG design, retries, backfills, SLAs) - Amazon S3 data lake design (partitioning, layout, lifecycle) - Data quality frameworks (Great Expectations or equivalent) - Data modeling (dimensional / Kimball, medallion layers) - Git/GitHub, CI/CD for data pipelines - Terraform - Python for automation and data processing Requirements - Desirable qualifications: - CDC patterns (DMS, incremental processing, MERGE upserts) - Streaming ingestion (Structured Streaming, Auto Loader) - AWS Glue Catalog / Unity Catalog - Metadata management (OpenMetadata) - BI integration (Superset, dashboarding) Company Description Founded by experienced entrepreneurs and engineers in 2016, Pismo is a technology company that provides a comprehensive processing platform for banking, card issuing, and financial market infrastructure and helps customers innovate and build the next generation of banking and payment solutions. Pismo joined Visa in 2024. Leveraging Visa’s solutions, our core platform, and an expanding suite of capabilities, Pismo addresses the technological challenges that large banks, marketplaces, and fintech companies face in migrating from legacy systems to more advanced technology in the market. Pismo’s cloud-based platform empowers firms to build and launch financial products rapidly, scaling as they grow to have a broader audience while keeping high security and availability standards. Pismo’s 500+ employees are located in more than 10 countries around the world.

Onebridge, a Marlabs Company, is a global AI and Data Analytics Consulting Firm that empowers organizations worldwide to drive better outcomes through data and technology. Since 2005, we have partnered with some of the largest healthcare, life sciences, financial services, and government entities across the globe. We have an exciting opportunity for a highly skilled Sr. Data Modeler to join our innovative and dynamic team. Sr. Data Modeler | About You As a Sr. Data Modeler, you are responsible for designing and governing high‑quality, scalable data models that bridge business needs with technical implementation. You bring deep experience translating complex, enterprise‑level requirements into conceptual, logical, and physical data models that support analytics, reporting, and operational workloads. You thrive at the intersection of data architecture, governance, and system optimization, ensuring data is secure, reliable, and fit for purpose. You collaborate closely with business, analytics, and engineering teams to align data strategy with organizational goals. You are detail‑oriented, strategic‑minded, and committed to building data foundations that support long‑term growth and compliance. Sr. Data Modeler | Day-to-Day - Design and maintain conceptual, logical, and physical data models that support enterprise data and analytics initiatives. - Analyze and optimize existing data models, databases, and pipelines to improve performance, scalability, and data usability. - Partner with business and technical stakeholders to translate requirements into standardized data structures and definitions. - Support data strategy and governance initiatives, including data quality standards, metadata management, and documentation. - Design and guide data migration and integration efforts, moving data from legacy systems to modern platforms. - Assist with implementing security, privacy, and compliance requirements, including access controls and regulatory standards such as GDPR or HIPAA. Sr. Data Modeler | Skills & Experience - 7+ years of experience in data modeling, data architecture, or enterprise data management roles. - Strong proficiency in SQL and hands‑on experience with data modeling tools such as ERwin, Visio, or similar platforms. - Experience working with cloud data platforms (AWS, Azure, or Google Cloud) alongside traditional RDBMS technologies (Oracle, SQL Server). - Strong understanding of data warehouse design, dimensional modeling, and ETL/ELT processes. - Experience supporting data governance, metadata management, and data quality initiatives in enterprise environments. - Familiarity with Big Data technologies and modern data processing architectures is preferred.