Role Description This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion). The Senior Cloud Data Engineer will be responsible for designing, developing, and implementing robust, scalable, and secure data pipelines for modern cloud platforms to support analytics and AI/ML needs at Arbitration Forums, Inc. This role will streamline data acquisition from different data sources and set up processes to ensure data quality and data security. Essential Duties and Responsibilities - Data Engineering & Pipeline Development: - Design, develop, and implement robust, scalable, and secure data pipelines in a cloud environment. - Build and manage ETL/ELT processes to efficiently move and transform large datasets from multiple data sources. - Implement secure data access, encryption, and data masking policies. - Develop automated processes to validate data quality and data accuracy. - Document and maintain data workflows and diagrams. - Work with data scientists and AI specialists to automate model deployment lifecycles (MLOps). - Data pipeline/warehouse management: - Configure and maintain cloud-based data warehousing solutions. - Optimize data warehouse storage strategies to support analytics and data science needs. - Set up monitoring tools and alerts to maintain data warehouse availability and reliability. - Troubleshoot, profile, and optimize data pipelines for performance issues to minimize latency. - Collaboration: - Work closely with data architects, data analysts and data scientists to understand their data needs and translate them into technical designs. - Mentor and guide junior data engineers, perform code reviews, and establish best practices for cloud data engineering. - Collaborate with DevOps and ITOps to implement CI/CD pipelines and robust DR strategies. Qualifications - Bachelor’s degree in computer science, Computer Engineering, Information Systems, or a related field. - 7+ years of experience in data engineering with a focus on cloud data engineering. - Technical Skills: - Profound understanding of major cloud platforms (AWS, GCP, Azure) and major cloud data platforms like Snowflake and Databricks. - Hands-on experience with data services offered by cloud platforms. - Expertise in programming languages such as Python, Java, or Scala with strong SQL skills. - Experience with ETL/ELT tools like Talend, DBT, Azure Data Factory, etc. - Experience with CI/CD tools like GitLab/GitHub. - Strong knowledge of data governance, data security, and compliance practices. - Experience supporting data science and machine learning operations. - Familiarity with data visualization and reporting tools (e.g., Power BI, Tableau). - Soft Skills: - Excellent analytical and problem-solving abilities. - Strong communication and interpersonal skills to collaborate with cross-functional teams. - Auto Insurance claims industry experience preferred. Americans with Disability Specifications - PHYSICAL DEMANDS: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is occasionally required to stand; walk; sit; use hands to finger, handle, or feel objects, tools or controls; reach with hands and arms; climb stairs; balance; stoop, kneel, crouch or crawl; talk or hear; taste or smell. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities required by the job include close vision, distance vision, color vision, peripheral vision, depth perception, and the ability to adjust focus. - WORK ENVIRONMENT: This is a fully remote position requiring reliable high-speed internet access and a dedicated workspace. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Liderar o design e avaliar a arquitetura de dados a ser utilizada para solução de um problema. • Construir pipelines robustos, escaláveis e de alta disponibilidade. • Resolver incidentes críticos e atuar como referência técnica. • Aplicar os padrões, as boas práticas e as políticas definidas pela equipe de governança de dados. • Implementar processos de observabilidade (monitoramento, alertas, logging). • Orientar Engenheiros Júnior, Pleno e Senior; realizar code reviews. • Contribuir na estratégia e roadmap da plataforma de dados.

• Design, develop, and maintain robust and scalable data pipelines using Apache Spark and cloud-native data services. • Build, optimize, and support ETL/ELT workflows to enable analytics, reporting, and downstream applications. • Implement and manage data solutions using Databricks, Delta Lake, and Unity Catalog. • Ensure data quality, reliability, and performance across large-scale and complex datasets. • Collaborate with cross-functional teams to gather data requirements and translate them into effective technical solutions. • Apply data engineering best practices related to scalability, security, monitoring, and maintainability. • Support the continuous improvement of data architecture, pipeline performance, and operational stability in a cloud environment.

**Responsibilities:** Design, build, and maintain scalable ETL/ELT pipelines using Databricks and AWS - Improve ingestion pipeline quality, reliability, scalability, and governance - Develop and optimize core data models and foundational data tables - Build analytics-ready datasets to support player insights, publishing analytics, esports analytics, and operational reporting - Implement data governance, data quality, lineage, and observability practices - Collaborate with product, analytics, engineering, and business stakeholders to support data-driven decision-making - Optimize large-scale data processing workflows for performance and cost efficiency - Support centralized player data models, viewer analytics, publishing activity systems, and operational metrics - Contribute to the unification of fragmented data ecosystems across multiple game teams and organizations - Build and maintain reliable orchestration workflows and scheduling systems - Participate in architectural discussions around scalability, governance, and data platform modernization