Data Operations Lead

The Data Operations Lead at Ryan is responsible for overseeing the UK Tax data strategy, managing the Data Governance Team, and ensuring data quality and compliance align with the company's business goals. This role involves implementing processes to enhance data integrity, creating and executing a comprehensive data strategy, and fostering collaboration across various departments to maximize data assets' value.

To qualify for the Data Operations Lead role at Ryan, candidates should have experience working with big data and a solid background in data strategy and delivery. Previous collaboration with stakeholders on data projects is preferred. While proficiency in SQL and other programming languages can be advantageous, the key requirement is a deep understanding of data stewardship and optimization.

At Ryan, we value professional growth and provide meaningful support for our employees, including a LinkedIn Learning subscription and tuition reimbursement after one year of service. As a Data Operations Lead, you’ll have access to these tools and the opportunity for an accelerated career path in a vibrant work environment that values innovation and excellence.

Ryan promotes a flexible work environment where you can enjoy the best of a hybrid workplace. As a Data Operations Lead, you'll be working mostly from home while enjoying the opportunities fostered by our Manchester office community. With our focus on employee well-being, including gym membership reimbursements and home office stipends, we encourage a healthy work-life balance.

The Data Operations Lead plays a critical role in aligning data governance practices with Ryan's broader business objectives. By ensuring data quality, compliance, and strategic execution of data initiatives, the Data Operations Lead significantly contributes to better decision-making and the overall performance of the organization.

When answering this question, draw on specific examples from your experience that demonstrate your ability to manage data quality, integrity, and accessibility effectively. Explain your approach to ensuring compliance and how you have implemented processes to enhance data usability.

To effectively answer this, discuss your methodology for assessing the value and impact of data initiatives. Highlight your experience in developing roadmaps and how you balance short-term needs with long-term strategic goals. Give examples of successful prioritization in past roles.

In your response, focus on your leadership style and mentoring techniques. Talk about your experiences providing feedback, fostering collaboration, and aligning team goals with overall business objectives. Provide examples of how you have supported your team’s professional growth.

Discuss your approach to fostering relationships with different teams, including regular meetings, communication techniques, and shared goals. Provide examples of how collaboration has led to successful project outcomes in your past roles.

Share a detailed example of a data strategy, outlining the goals, processes, and outcomes. Discuss how you identified business needs and ensured stakeholder buy-in, including metrics you used to measure success.

Mention the specific tools you have used for data governance, including any preferred software or methodologies. Discuss how these tools have helped improve data quality and integrity in your previous roles.

Explain your approach to managing resistance by focusing on communication and education. Share techniques you’ve used to provide clarity on data project benefits, helping stakeholders understand the value of data governance initiatives.

Provide a specific scenario where you translated complex data findings into understandable insights for non-technical stakeholders. Highlight the methods you used to convey these insights and the positive outcome on decision-making.

Discuss a few challenges such as data silos, compliance issues, or varying data quality standards, and focus on the strategies you devised to overcome these obstacles, including examples that emphasize your problem-solving abilities.

Share your insights on the evolving landscape of data management, touching on technology trends like AI, machine learning, or data democratization. Discuss how you plan to adapt to these changes in your role as Data Operations Lead.