Finance Data Engineering & Analytics Manager

As a Finance Data Engineering & Analytics Manager at Shield AI, you will be responsible for leading the implementation of a comprehensive data strategy that enhances data quality and governance. You'll utilize your SQL, Python, and Excel expertise to analyze data and generate insights, design and maintain a Microsoft Fabric data warehouse, and automate data workflows. Your role also includes developing Power BI dashboards that provide real-time financial insights to key stakeholders, and you'll collaborate with cross-functional teams to align financial data with broader intelligence frameworks.

For the Finance Data Engineering & Analytics Manager role at Shield AI, candidates should have at least 5 years of experience in business intelligence or financial analytics positions. Advanced proficiency in Power BI, SQL, and Excel is crucial, along with skills in ETL processes and data integration. Familiarity with cloud platforms like Azure and strong analytical abilities are also necessary to translate complex data into actionable insights effectively.

Experience in Python is particularly beneficial for a Finance Data Engineering & Analytics Manager at Shield AI, as it allows for more sophisticated data management, automation tasks, and analytics. Python can enhance ETL processes and facilitate the integration of unmanaged data sources, ultimately leading to more robust financial insights and streamlined reporting processes—essential aspects of the role.

The salary range for a Finance Data Engineering & Analytics Manager at Shield AI varies from $120,000 to $185,000 a year. Compensation packages may also include bonuses, benefits, equity, and other perks, depending on the role and location. Factors such as skill set, experience, and specific work location will influence the final offer.

At Shield AI, the work environment is dynamic and collaborative, centered around innovation and impactful technology. As a Finance Data Engineering & Analytics Manager, you'll work with a talented team focused on leveraging advanced analytics to support the company’s mission. With a strong emphasis on data quality and decision-making, you can expect an engaging atmosphere where your contributions will significantly influence the organization’s strategic direction.

In your response, emphasize your past projects where you developed or implemented data strategies. Highlight specific methodologies you used, challenges you faced, and how you guided the team to enhance data quality and accessibility, relevant to the expectations of Shield AI.

Discuss the practices you put in place to maintain high data integrity, such as rigorous ETL processes, validation checks, and the use of automated tools. This will demonstrate your attention to detail and commitment to producing accurate financial insights.

Be sure to mention your proficiency in Power BI, SQL, Python, and advanced Excel. Provide examples of how you used these tools in your previous positions to create reports, dashboards, or perform analytics, illustrating your capability to drive financial insights at Shield AI.

Discuss your teamwork experiences and how you communicate complex data insights to technical and non-technical audiences. Highlight the importance of collaboration at Shield AI and how your skills will facilitate effective partnerships among various departments.

Share your strategies for effective data visualization, focusing on how you select or design visual tools like dashboards that present data clearly. Mention your experience with Power BI or similar tools relevant to Shield AI, emphasizing how you ensure stakeholders can easily interpret the data.

Prepare to discuss a specific project where you navigated through a challenging dataset, the analytical techniques you employed, and how those insights led to actionable decisions. Tailor this example to demonstrate your capacity to handle the responsibilities expected in the Finance Data Engineering & Analytics Manager role.

Talk about resources you use to keep your knowledge current, such as industry publications, online courses, or professional groups. This shows your dedication to continuous learning and align with the innovative culture at Shield AI.

Use the STAR method (Situation, Task, Action, Result) to outline a specific challenge you encountered, how you and your team addressed it, and the successful outcome. This approach will exemplify your problem-solving skills relevant to the role.

Express your understanding of how automation can improve efficiency, reduce errors, and enable real-time data insights. Discuss any tools or scripts you’ve implemented to streamline processes, emphasizing how this aligns with Shield AI’s goals.

Articulate your passion for defense technology and how it intersects with your expertise in finance and data analytics. Highlight your alignment with Shield AI's mission and your excitement about contributing to a company that prioritizes the safety of service members and civilians.