Mid-Level Data Engineer - NTIA Contract

The Mid-Level Data Engineer role at Expression involves collaborating with program managers and product owners to create products that resonate with customers, leading teams through the complete data science lifecycle, designing and documenting software code, and building robust data pipelines. Additionally, you’ll contribute to white papers, partake in case studies, and mentor new talent in an innovative environment.

To apply for the Mid-Level Data Engineer position at Expression, candidates should have over 5 years of experience in data engineering or data science, along with a Bachelor’s degree in relevant fields, or 8 years of experience with a Master’s degree or 5 years with a PhD. Current Security+ certification (or the ability to obtain it soon) and proficiency in programming languages like Python and SQL are also essential.

A Mid-Level Data Engineer at Expression possesses significant experience but may not yet have the depth of leadership responsibilities required of senior roles. While you will lead initiatives and projects, the level of strategic direction and oversight typically associated with a senior position, such as defining long-term vision for technology and mentoring across multiple teams, may be more prominent at that level.

A successful Mid-Level Data Engineer at Expression must be proficient in programming languages such as Python, JavaScript, and SQL. Familiarity with data architectures like Data Lake, experienced in ETL processes, and knowledge of Azure solutions and machine learning methodologies are highly beneficial, alongside a good grasp of tools such as Databricks and ElasticSearch.

Expression emphasizes a culture of 'Perpetual Innovation' which fosters creativity and collaboration among its teams. As a Mid-Level Data Engineer, you will be encouraged to share ideas, engage in continual learning, and participate in exciting projects that have a real impact on the national security landscape, all while enjoying a supportive work environment.

Discuss specific projects where you have designed or managed data pipelines, detailing the technologies used and your role in the process. Demonstrating your understanding of both batch and streaming data will be essential.

Share examples that highlight your communication skills and ability to work in diverse teams. Talk about specific instances where you have influenced or contributed to the collective goals of data scientists, architects, and product owners.

Provide a concise summary of your proficiency in programming languages like Python and Java, illustrating with examples of how these skills have enabled you to solve complex problems or improve data processes.

Use the STAR method (Situation, Task, Action, Result) to present a specific challenge, the steps you took to tackle it, and the impact of your solution on the project or organization.

Describe your hands-on experience with various databases, explaining how you designed ETL processes for them, and any challenges you encountered during implementation.

Articulate your methods for continual learning, whether it be online courses, participation in relevant forums, or attending industry conferences. Mention specific technologies you’ve explored recently.

Discuss your approach to testing, documentation, and performance reviews. Emphasize any frameworks or methodologies you adhere to for maintaining high-quality outputs.

Share a project where you incorporated machine learning techniques. Detail your role, the technologies used, and the outcomes achieved.

Explain your organizational skills and any tools you use to manage your workload. Provide an example when you successfully met a deadline while maintaining the quality of your work.

Express your enthusiasm for Expression’s commitment to innovation and support of national security. Link your career aspirations and values with the company’s mission and how you envision contributing to their Data Science Department.