Position Summary The Fedcap Group (TFG) is seeking a transformational and highly strategic Data Engineer to architect and lead the enterprise data warehouse, and data capabilities. This role is instrumental in enabling operational excellence, mission alignment, and scalable growth across TFG’s international network. Reporting to the Head of Data and Analytics. Goals of the Position (Hands on Sr. Data Engineering) The Sr. Data Engineer will: - Deliver Reliable, Analytics-Ready Data Models - Design and implement Snowflake/dbt data models that enable BI dashboards, advanced analytics, and AI workloads. - Build Secure and Compliant Data Infrastructure - Implement role-based access, data masking, and governance controls in both ADF and snowflake, ensuring compliance with organizational and regulatory delivery. - Lead development of dbt and transformation workflows - Write, test, and deploy dbt models and transformations with automated quality checks. - Build reusable macros and packages to accelerate pipeline delivery. - Ensure performance and cost optimization - Tune Snowflake queries and warehouses to improve efficiency and reduce costs. - Build monitoring and alerting frameworks to detect performance or data quality issues. - Enable end to end Data pipeline - Build ingestion (Snowpipe, Streams, Tasks) and transformation workflows that move data from raw (Bronze) to curated (Gold) layers. - Deliver pipelines that are automated, resilient, and production ready. - Directly Support Business & Analytics Teams - Partner with stakeholders to understand data needs and translate them into solutions. - Take ownership from requirements to delivery, ensuring solutions are deployed accurately and are following engineering standard frameworks. Key Responsibilities - Collaborate with the Head of Data and Analytics to implement the enterprise Medallion Architecture (Bronze → Silver → Gold) - Design, build, and maintain data ingestion pipelines in Azure Data Factory (ADF) to move data from diverse sources into Azure Data Lake Storage Gen2 (Bronze). - Configure and manage secure integrations between Azure and Snowflake, including external stages, storage integrations, and automated ingestion patterns (Snowpipe, Streams, Tasks). - Develop and optimize Snowflake data models (fact, dimension, staging tables) aligned to Bronze–Silver–Gold architecture and business KPIs. - Implement role-based access control (RBAC), data masking, and row/column-level security in Snowflake to ensure data privacy and compliance. - Build and maintain a modular dbt framework, including models, macros, tests, and snapshots, to enforce data quality and accelerate transformations. - Create and manage CI/CD pipelines for dbt using GitHub Actions or Azure DevOps, ensuring reliable deployments across environments. - Write and optimize complex SQL and Python scripts to automate workflows, monitor data pipelines, and troubleshoot production issues. - Implement data validation, quality checks, and monitoring frameworks to ensure freshness, accuracy, and reliability of data products. - Collaborate directly with BI, Analytics, and Data Science teams to deliver curated, business-ready datasets. - Take end-to-end ownership of assigned data engineering projects: requirements -design - build - deploy - support. - Document pipelines, transformations, and models to ensure reproducibility and team-wide adoption Qualifications Education & Certification - Bachelor’s degree in information systems, Computer Science, Engineering, or related field. - Advanced degrees in related fields are plus, however hands-on experience is strongly preferred. - Snowflake Snowpro Advanced Data Engineer / Architect certification (Preferred). - Data Governance certifications (preferred). Professional Experience - 5+ years of proven experience in data engineer roles. - Deep expertise in enterprise system implementations, data lifecycle management, modular framework and data platform architecture. - Strong hands-on experience with dbt , Azure and snowflake are a must. - Demonstrated ability to design and implement scalable, secure and modular data pipeline. - Experience with data quality frameworks, lineage and governance practice. - Track record of delivering end-to-end data solutions in cloud environments. Success Metrics (First 6–12 Months) - Reliable Ingestion: Design and deploy at least 10 production-ready ADF pipelines that ingest data into ADLS and Snowflake with metadata-driven, reusable templates. - Modular Framework Adoption: Establish a dbt modular framework (Bronze → Silver → Gold) with 50+ tested models and reusable macros adopted across the team. - Data Quality: Implement automated dbt tests and validation frameworks achieving 95%+ test coverage for curated (Silver/Gold) datasets. - Performance & Cost Optimization: Reduce Snowflake warehouse costs by 15–20% through query optimization, partitioning, and warehouse right-sizing. - Security & Compliance: Implement role-based access (RBAC) and masking policies in Snowflake with zero security audit findings. - Pipeline SLAs: Deliver pipelines that consistently meet agreed SLAs (e.g., data availability within X hours of source refresh). - Business Impact: Enable at least 5–10 critical BI dashboards or analytics use cases by delivering curated, business-ready datasets

Role Description We are looking for a Principal, Data Analyst seeking to work with our clients to shape business and data strategy. You are highly analytical and excited about applying a quantitative framework to business problems through performing analysis, data mining, predictive modeling, business forecasting, applied statistics, and more. You are comfortable with presenting your approach to Product Managers, Engineers, Marketing, Sales, Finance and working with them to execute a data-driven business process. At DEPT®, we pride ourselves on our pragmatic, engineering approach to making data work for the business. Qualifications - Expertise in applications of experimentation and measurement - Data-driven curiosity that leads to deep, meaningful, and actionable insights for our clients - A vision for reusable, scalable data pipelines and models as well as the skill to execute on building them - Compelling and cohesive storytelling that applies analytics to convince clients and DEPTsters on tactical decisions, in addition to building narratives about the need for analytics - Clear communication of context, recommendations, and rationale to relevant internal and/or external stakeholders to drive earn buy-in - A client delivery mindset with the ability to take a step back and ensure that work being done is maximizing client value - Awareness of industry trends, how they affect our work and introduction of new ideas into our current workflow Requirements - 5+ years of applied analytics in sales, finance, marketing, product, engineering - 5+ years of discovery and assessment of a client’s data portfolio, data tools, and data applications - 3+ years of data management and consulting experience - Experience with cloud platforms such as AWS, GCP, Azure to use/deploy analytics solutions - Strong working knowledge of SQL. NoSQL is a plus - Experience in at least one or more languages for applied statistics, data analysis, and machine learning - Python, R, Matlab, SPSS - Manage a data ecosystem including ETL, data governance, reporting and insights - Ability to take a project from RFP/SOW/BRD to delivery: project management, requirements gathering, data architecture, workflow management, quality assurance, reporting and visualization, presentation - Interest in mentoring junior colleagues on process, analysis, deliverables, client communication, and management skills Benefits - Healthcare, Dental, and Vision coverage - 401k plan, plus matching - PTO - Paid Company Holidays - Parental Leave

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. We are seeking a Senior Data Engineer / Software Developer to support and scale our AI‑driven data platforms. This role focuses on building robust AI pipelines, shared tooling, and engineering standards that enable consistent, high‑quality generation and consumption of advanced analytics outputs across the organization. The engineer will play a key role in strengthening the technical foundation that supports analytics and oncology insights. Key Responsibilities Business Drivers - Collaborate with data scientists, machine learning engineers, and analytics teams to provide technical direction for AI and advanced analytics platforms - Work closely with data warehousing, data engineering, and cloud platform teams to design optimal architectures for AI‑driven data solutions - Enable the scalable use of AI‑generated outputs (e.g., ML predictions, extracted signals, model outputs) in conjunction with structured data to support analytics and oncology insights - Partner with senior management and stakeholders to communicate AI system capabilities, implementation approaches, assumptions, and limitations in clear, non‑technical language Technical Responsibilities - Participate in the full lifecycle of AI and data platform solutions, including planning, design, implementation, deployment, monitoring, and ongoing maintenance - Design, build, and maintain production‑grade AI pipelines, shared frameworks, and supporting services in the cloud (e.g., AWS, GCP, Azure; Azure preferred) - Design, test, and maintain AI‑enabled applications and services using modern software engineering and testing methodologies - Perform code reviews and help define engineering and AI code standards to ensure high‑quality, scalable, and maintainable solutions - Develop and maintain scalable data and AI pipelines using Python and supporting technologies - Design and implement data architectures that support downstream analytics and access by McKesson analysts and AI data consumers Drive innovation - Develop reusable engineering solutions to support AI workloads, model execution, inference pipelines, and integration into downstream data products - Evaluate new AI‑related tools, frameworks, and platforms to improve scalability, reliability, and developer productivity prior to broader adoption - Experience supporting AI or machine learning solutions in healthcare, oncology, genomics, or medical data domains is preferred but not required Minimum Requirement - Degree or equivalent and typically requires 7+ years of relevant experience. Education - A degree in a quantitative field such as Statistics, Machine Learning, Mathematics, Computer Science, Economics, Epidemiology or any other related field - Master’s Degree or higher preferred Critical Skills - 3+ years of relevant experience in data engineering or software development roles supporting analytics or AI‑enabled solutions; healthcare experience preferred - Proficiency in Python and SQL, with demonstrated experience developing and maintaining reliable, production‑grade data pipelines and analytical datasets - Experience building and supporting internal tools or applications used for data validation, monitoring, review, or operational analytics workflows - Working knowledge of application integration patterns, including service‑based architectures and data access layers that support UI‑driven tools - Hands‑on experience using Databricks for data processing, analytics development, and collaboration with data science or analytics teams - Experience working within Microsoft Azure environments, applying standard engineering practices to deliver maintainable, well‑documented solutions Additional Skills - Familiarity with machine learning or AI concepts, including model lifecycles, inference workflows, and integration of model outputs into analytics or data products - Exposure to Natural Language Processing or other unstructured data workflows, such as text ingestion, extraction, or downstream signal consumption - Experience with NoSQL or semi‑structured data stores and alternative data persistence patterns - Experience with analytics visualization tools or reporting solutions, and familiarity with modern scripting or web technologies used to support internal tools We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here. Our Base Pay Range for this position $136,300 - $227,100 McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind: McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application. McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates. McKesson job postings are posted on our career site: careers.mckesson.com. McKesson is an Equal Opportunity Employer McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page. McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com or (Canada) Accessibility@mckesson.ca. Resumes or CVs submitted to this email box will not be accepted. Join us at McKesson!

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!