Data Steward

As a Data Steward at Smartdesc, your key responsibilities include validating product data to ensure its completeness and accuracy, coordinating with data owners to resolve discrepancies, and collaborating with stakeholders for data-related inquiries. You will also create and manage reports on product data and the progress of launches, enhancing data quality across multiple systems as part of our migration program.

To qualify for the Data Steward position at Smartdesc, candidates should have a minimum of 5 years of experience in data management, advanced proficiency in data tools like Excel, and familiarity with various data management systems. Additionally, experience in ecommerce or retail environments is beneficial as it equips candidates with the understanding of product data lifecycles crucial for this role.

Smartdesc values the professional growth of its employees, including Data Stewards. We offer opportunities for training and certification at no cost, and promote from within. This commitment to development ensures our team members are equipped with the latest skills in data management and technology, enabling them to excel in their roles.

As a Data Steward at Smartdesc, you'll work in a flat management structure that fosters a collaborative and supportive atmosphere. We emphasize autonomy and integrity, allowing our team members the freedom to excel in their roles. With a retention rate of 98%, Smartdesc is dedicated to maintaining a fun, enjoyable work environment where everyone can thrive.

In the Data Steward role at Smartdesc, you will utilize advanced tools like Excel to maintain and manage data inputs and outputs. Additionally, familiarity with various data management systems will be important, as you may also create dashboards and reports to track product data status and analyze discrepancies across systems.

The role of a Data Steward in ensuring data quality involves validating data accuracy, completing data checks, and coordinating with data owners to resolve discrepancies. A good answer should highlight your experience with data validation techniques and how you have improved data quality in previous roles.

When approaching problem-solving in data management, I focus on identifying the core issues affecting data quality. I would discuss methods I've used to investigate data discrepancies and the analysis processes involved. Providing specific examples from past experiences will help demonstrate your analytical skills.

In my previous roles, I've gained extensive experience with data management tools like Excel for data analysis and reporting. I would elaborate on my proficiency in creating dashboards, managing large datasets, and using other tools that support data integrity. Mentioning specific scenarios helps illustrate your hands-on experience.

To ensure consistency across platforms, I prioritize validating data against established standards and guidelines. I would highlight strategies I've used to coordinate with different teams to address data discrepancies and maintain uniformity, such as implementing checklists or automated processes.

Upon identifying a data quality issue, I would assess the severity and nature of the problem, then collaborate with relevant stakeholders to rectify it efficiently. Sharing specific techniques I've employed, like root cause analysis or proactive monitoring, can enhance my response.

Staying organized while managing multiple data sources involves utilizing project management tools and effective documentation practices. I would discuss my approach to prioritizing tasks, setting deadlines, and maintaining clear records, including examples of tools I've used for tracking and reporting data.

My experience in stakeholder communication includes clarifying data requests, addressing issues, and aligning project timelines. I would convey how I adapt my communication style based on the audience, using examples that showcase flexibility and clarity in conversations.

In my previous position, I led a project to migrate data across platforms, improving data quality by 30%. I would detail the process, the challenges faced, and the impact of our efforts on business operations and decision-making, as metrics can substantiate my success.

I utilize various analytical methods, such as cross-referencing data against source documents and conducting trend analysis to identify discrepancies. Explaining the tools and techniques I've utilized can demonstrate my analytical skills clearly.

Data stewardship is crucial in ecommerce and retail as accurate product data drives sales and enhances customer experience. I would emphasize the direct correlation between data quality and business success while referencing real-world impacts of data management practices.