Senior-Level Data Engineer

As a Senior-Level Data Engineer at Redhorse Corporation, your main responsibilities include configuring and ingesting structured, unstructured, and semi-structured data repositories, maintaining operational aspects of data transfers, automating configuration management, and engaging with multiple functional groups to create innovative data solutions. You'll also be responsible for identifying areas for optimization and ensuring the security and health of the data environment.

To qualify for the Senior-Level Data Engineer position at Redhorse Corporation, you should possess a Bachelor’s degree with at least 7 years of relevant experience, or a Master’s degree with 5 years of experience. Additionally, expertise in big data systems, cloud technologies such as AWS or Azure, and a strong coding background are crucial. An active Top Secret (TS) security clearance with SCI eligibility is also required.

The Senior-Level Data Engineer at Redhorse Corporation will work with a variety of technologies including big data systems like Apache Spark and Databricks, cloud environments such as Amazon Web Services (AWS) and Microsoft Azure, and various ETL tools for data processing. Your role will involve leveraging these technologies to build robust data pipelines and innovate solutions for national security.

Redhorse Corporation encourages continuous learning and professional development for their Senior-Level Data Engineers through training programs, workshops, and access to the latest technologies. You'll have opportunities to engage in innovative projects that contribute to your growth while staying updated on industry trends and practices.

A Senior-Level Data Engineer at Redhorse Corporation plays a critical role in advancing data-driven decision-making across the DoD. By designing and implementing robust data solutions, you'll directly impact national security initiatives and help shape the future of data management and analytics within the department.

When answering this question, highlight your proficiency in designing and managing data pipelines. Discuss specific tools or technologies you've used, any optimization strategies you implemented, and the outcomes of your work. Provide examples that demonstrate your problem-solving skills and technical expertise.

Focus on your understanding of security protocols and the importance of following best practices when handling data. Explain specific measures you've implemented, such as encryption, access controls, and compliance with DoD Security Technical Implementation Guides (STIGs). Show how these practices safeguard sensitive information.

Share specific projects or tasks where you've effectively utilized Apache Spark or similar big data technologies. Emphasize your ability to process large datasets, manage distributed data systems, and collaborate with others to achieve data-driven results.

Use the STAR (Situation, Task, Action, Result) method to discuss a particular challenge, the steps you took to address it, and the successful outcome. Highlight your analytical thinking, problem-solving abilities, and any innovative approaches you employed to find a solution.

Explain your commitment to continuous learning through various channels such as online courses, industry events, or professional networks. Mention any blogs, publications, or communities you follow that keep you informed about the latest trends and technologies in data engineering.

Discuss your hands-on experience with cloud platforms like AWS or Azure. Talk about specific services you've used for computing, storage, or data processing, and how those services contributed to the projects you worked on, demonstrating your familiarity with cloud environments.

When answering, emphasize the ETL (Extract, Transform, Load) process's role in data management. Explain how it facilitates the integration of data from various sources, prepares it for analysis, and ensures data quality and consistency, which are critical for informed decision-making.

Discuss your preferred coding languages and how they relate to the tasks of a Senior-Level Data Engineer. Mention the strengths of these languages for data manipulation, automation, or analytics, providing examples of how you’ve successfully used them in past projects.

Share your strategy for prioritizing tasks, such as utilizing project management tools, setting clear deadlines, or breaking down projects into manageable parts. Show how you remain organized while addressing urgent needs without sacrificing quality.

When responding, express your enthusiasm for Redhorse Corporation’s mission and the opportunity to contribute to national security initiatives. Highlight how your skills and values align with the company's goals and your eagerness to be part of a team that drives innovation in data engineering.