Senior Data Analyst

Chervon is one of the world’s largest power tool and outdoor power equipment manufacturers with a rich history of innovation. Chervon’s commitment to build a better world by building better tools is evident in the products we manufacture and our green approach to manufacturing. We design, engineer and market power tools and outdoor power equipment within our brand portfolio- EGO, FLEX and SKIL and for other highly respected private brands. With world-class R&D, design, manufacturing, supply chain, marketing, sales, and service teams throughout the world, we do it all.

Summary of Responsibilities:

As the Senior Data Analysis, your primary focus will be on designing and implementing DataOps practices within our organization. You will serve as a key resource for resolving complex technical issues related to data infrastructure and processes. Leveraging your expertise in data modeling, ETL processes, data warehousing solutions, and AWS cloud services, you will lead initiatives to enhance operational efficiency and ensure data reliability and availability through the implementation of DataOps methodologies.

Key Responsibilities:

• Serve as a primary resource for resolving complex technical issues related to data infrastructure and processes.

• Collaborate closely with the IT team in China to address escalated technical issues, ensuring timely resolution and minimal impact on operations.

• Conduct routine system checks and maintenance to optimize data infrastructure performance and proactively identify potential issues.

• Utilize your deep understanding of data modeling, ETL processes, and data warehousing solutions to enhance data analysis capabilities and drive informed decision-making.

• Facilitate training sessions for team members, equipping them with knowledge of DataOps principles and best practices.

• Develop, maintain, and update comprehensive documentation, including troubleshooting guides, Knowledge Base articles, and best practices for data infrastructure and processes.

• Lead the design and implementation of DataOps practices, overseeing data integration, automation, and monitoring processes to streamline operations and enhance data reliability and availability.