Your role at DynatraceAbout the Role: Dynatrace is seeking a high-impact Telemetry Pipeline Specialist to serve as the business and technical evangelist for the next generation of data-driven Observability. This is a specialist role focused on the intersection of Bindplane, OpenTelemetry (OTel), and Enterprise Data Governance. You will partner with our Global Sales and Customer Success teams to help organizations navigate the complexities of data explosion in hybrid and AI-native environments, ensuring they achieve high-signal observability while maintaining absolute control over their telemetry costs and routing. Domain Expertise & Solution Leadership - Act as a subject matter expert in log management and observability - Stay current with OpenTelemetry, cloud logging, and pipelines - Lead proof of concepts and demonstrate technical value Competitive Strategy & Value Selling - Execute competitive displacement strategies - Build ROI and economic value cases - Position Dynatrace effectively in enterprise environments Technical Solution Guidance - Advise on telemetry pipelines (OpenTelemetry, Fluentd, Logstash) - Support Kubernetes, serverless, and cloud ecosystems - Optimize data routing and analytics strategies Customer Adoption & Growth - Drive platform adoption and usage - Deliver best practices and technical workshops - Improve consumption and customer outcomes Collaboration & Pipeline Development - Build pipeline through channels, events, and outbound - Collaborate cross-functionally with sales, engineering, and marketing - Maintain CRM accuracy and forecasting discipline What will help you succeedQualifications & Requirements: - Experience: 5+ years in sales or presales roles, with at least 3 years focused on log management, telemetry pipelines, or data streaming environments Domain Expertise: - Deep understanding of telemetry routing and edge processing (Bindplane, Fluent Bit, or similar) - Familiarity with cloud-native ecosystems (AWS, Azure, GCP, Kubernetes) and event streaming platforms (Kafka, Kinesis, Pub/Sub) - Sales Execution: Experience supporting complex enterprise sales cycles and influencing both technical and executive stakeholders; Ability to articulate “Data Gravity” and - “Ingest Economics” and translate them into executive-level value (CIO/CFO) - Competitive Knowledge: Familiarity with observability and pipeline competitors such as Splunk, Datadog, Elastic, or Cribl - Enablement: Ability to scale impact through field enablement, play development, and technical evangelism - Education: Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience Preferred Skills - Experience with Cribl LogStream or Splunk Heavy Forwarders for displacement strategies. - Familiarity with FinOps principles (matching telemetry spend to business value). Why you will love being a Dynatracer - Dynatrace is a leader in unified observability and security. - We provide a culture of excellence with competitive compensation packages designed to recognize and reward performance. - Our employees work with the largest cloud providers, including AWS, Microsoft, and Google Cloud, and other leading partners worldwide to create strategic alliances. - You'll get to work at the forefront of innovation with Dynatrace Intelligence—the industry's first agentic operations system. Bringing together deterministic and agentic AI, it helps teams understand what's happening, why it matters, and what to do next— automatically. - Over 50% of the Fortune 100 companies are current customers of Dynatrace. Compensation and Rewards

Role Description Na ROIT, acreditamos que dados são um dos principais ativos para transformar negócios. Estamos construindo uma plataforma de dados moderna, escalável e preparada para suportar produtos analíticos, inteligência Artificial e soluções que impactam milhares de empresas. Buscamos um(a) Tech Lead | Data Platform para liderar tecnicamente essa evolução. Essa pessoa será responsável por: - Definir a arquitetura da plataforma; - Estabelecer padrões de engenharia; - Apoiar o crescimento técnico da equipe; - Garantir que nossas soluções sejam escaláveis, confiáveis, eficientes e preparadas para os desafios do futuro. Procuramos alguém com perfil hands-on, que goste de resolver problemas complexos, tomar decisões arquiteturais e construir produtos de dados de alta qualidade. Qualifications - Experiência sólida em Engenharia de Dados, atuando como Tech Lead ou referência técnica de equipes; - Domínio de Python para desenvolvimento de aplicações e pipelines de dados; - Experiência prática com Google Cloud Platform (GCP); - Conhecimento sólido em BigQuery, Cloud Storage, Pub/Sub, Cloud Run e Dataproc; - Experiência com arquitetura de Data Lake, Data Warehouse e Data Marts; - Conhecimento avançado em bancos de dados SQL e NoSQL; - Experiência com arquiteturas distribuídas, microsserviços e arquiteturas orientadas a eventos; - Vivência com CI/CD, Git e Infraestrutura como Código (Terraform ou similar); - Experiência com monitoramento, observabilidade e troubleshooting de pipelines de dados; - Capacidade de conduzir discussões técnicas, definir padrões de engenharia e apoiar a evolução técnica da equipe. Requirements - Experiência com Apache Spark (PySpark); - Experiência com Apache Airflow ou orquestradores de workflows; - Vivência com processamento de dados em tempo real (streaming); - Experiência em ambientes de alta volumetria de dados; - Conhecimento em arquiteturas Lakehouse; - Experiência com plataformas de Inteligência Artificial e Machine Learning; - Vivência com otimização de custos em ambientes cloud (FinOps). Benefits - Python - Google Cloud Platform (GCP) - BigQuery - Dataproc (PySpark) - Cloud Run - Pub/Sub - Cloud Storage - GitHub / Bitbucket - Arquiteturas orientadas a eventos

• Research new reasoning algorithms and models • Develop model benchmarking processes and tools • Build effective and efficient ML data pipelines • Adjust frameworks and interfaces to accelerate machine learning development • Develop the infrastructure for data augmentation pipelines and synthetic data generation • Collaborate with other teams to understand their pain points and priorities to define milestones of the corresponding roadmaps • Derive practical solutions and integrate them with the results of other teams to provide the best overall resolution

Role Description CTG is seeking to fill a Data Engineer (Microsoft Fabric, Spark/PySpark) position for our client. Join a dynamic data engineering team responsible for designing and delivering modern lakehouse solutions that support enterprise analytics and data-driven decision-making. This role focuses on building scalable data pipelines, implementing Microsoft Fabric lakehouse architectures, and developing Spark/PySpark solutions that integrate data from multiple enterprise systems. Candidates with Databricks or comparable lakehouse platform experience are also encouraged to apply. Location: Remote Duration: 7 months Duties: - Design, develop, and support enterprise data engineering solutions using Microsoft Fabric. - Build and maintain scalable lakehouse architectures, including schema design and data organization. - Develop Spark Notebooks and Spark/PySpark applications for data ingestion, transformation, and processing. - Create and orchestrate reliable data pipelines integrating data from numerous enterprise source systems. - Design and manage file structures, metadata, and storage organization within lakehouse environments. - Implement and maintain security, permissions, and governance across Microsoft Fabric workspaces. - Optimize data processing performance and troubleshoot production issues. - Collaborate with architects, analysts, and business stakeholders to deliver high-quality data solutions. - Participate in Agile development processes, code reviews, testing, and CI/CD deployment activities. - Contribute to continuous improvement of data engineering standards and best practices. Qualifications - Strong experience with Microsoft Fabric, including: - Lakehouse architecture and implementation - Spark Notebook development - Schema design and management - File and folder structure management - Security, permissions, and access management - Hands-on Spark or PySpark development experience. - Experience building and orchestrating enterprise data pipelines. - Experience integrating data from multiple source systems (10+ preferred). - Strong understanding of lakehouse data structures and data organization. - Excellent analytical, troubleshooting, and problem-solving skills. Requirements - Databricks lakehouse engineering experience or experience with other modern lakehouse platforms (preferred). - Experience with cloud-based data engineering environments. - Jira, Kanban, and Agile methodologies. - Jenkins and CI/CD pipeline implementation. - Experience with enterprise data warehouse platforms such as Snowflake or Teradata. Experience - 5+ years of experience in Data Engineering, Data Warehousing, or related disciplines. - Proven experience designing and implementing scalable enterprise data platforms. - Strong hands-on experience with Spark/PySpark for large-scale data processing. - Experience developing modern lakehouse solutions using Microsoft Fabric, Databricks, or similar technologies. - Experience integrating and managing large, complex datasets from multiple enterprise systems. - Strong understanding of data modeling, ETL/ELT processes, and enterprise data architecture. - Experience working within Agile software development environments. Education - Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or a related technical field. - Equivalent combination of education and relevant professional experience will also be considered. - Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. To Apply To be considered, please apply directly to this requisition using the link provided. Kindly forward this to any other interested parties. Thank you! The expected base salary for this position ranges from $50.00 to $55.00/hour. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, market factors, and where applicable, licensure or certifications obtained. In addition to salary, a competitive benefit package is also offered.