Data Engineer Junior/Mid Level

As a Junior/Mid-Level Data Engineer at our company, you will work on manipulating data and data flows, supporting ETL processes, and ensuring maintenance and integrity of databases. You'll develop complex data flows and troubleshoot challenges in a fast-paced environment, gaining hands-on experience with large-scale data.

To qualify for the Junior/Mid-Level Data Engineer position, candidates should have at least 5 years of experience in software engineering and ETL processes, along with a degree in Engineering or equivalent experience. Familiarity with languages like Java, Python, and SQL, among others, is essential.

A Junior/Mid-Level Data Engineer at our company should be proficient in languages such as Java, Python, and SQL, and have experience with GPU processing, data visualization tools, and database methodologies. Familiarity with servers, cloud infrastructure, and data science frameworks will also be beneficial.

The salary range for the Junior/Mid-Level Data Engineer position at our company is between $89,250 and $195,500 annually, depending on experience and qualifications.

Candidates can expect to work in a fast-paced and continually evolving environment that emphasizes continual process improvement and proactive problem-solving. Collaboration and dynamic teamwork are hallmarks of our work culture.

Yes, an active TS/SCI clearance with an appropriate polygraph is required for the Junior/Mid-Level Data Engineer position at our company to ensure security compliance.

Career growth opportunities for a Junior/Mid-Level Data Engineer at our company are abundant. You will have the chance to take on new projects, work with advanced technologies, and develop specialized skills that can lead to senior engineering roles or managerial positions.

In discussing your experience with ETL processes, focus on specific examples where you have contributed to the design and implementation of ETL workflows. Highlight tools you’ve used, challenges you faced, and how you ensured data integrity throughout the process.

When answering this question, list the programming languages you are proficient in, such as Java, Python, or SQL. Provide examples of projects where you used these languages, and how they contributed to the success of the data-driven tasks.

To ensure data quality, describe techniques like data validation, cleansing, and regular audits that you apply throughout the lifecycle of data. Mention any tools you use and how they affect the projects positively.

Share a detailed example of a complex data mapping project. Discuss the goals of the project, the steps taken to create the mapping, any challenges encountered, and how you overcame them to achieve successful results.

Discuss your familiarity with various relational databases such as Oracle or MySQL. Provide specific instances where you have designed, implemented, or optimized database structures for better data accessibility.

When troubleshooting an ETL process failure, explain your systematic approach: reviewing logs, inspecting data lineage, and testing various components. Offer an example of a past situation and how you resolved it efficiently.

Talk about tools and techniques you prefer for data visualization, such as Tableau or ElasticSearch. Describe how you use visualization to derive insights and support decision-making.

Share the ways you stay informed about emerging technologies, such as attending conferences, following relevant blogs, or participating in online courses. Highlight any specific innovations that excite you.

Describe a project where you implemented machine learning methodologies. Focus on the objectives, types of algorithms used, how data was processed, and the outcomes that were achieved through model predictions.

Highlight skills like programming proficiency, analytical thinking, and familiarity with databases as essential for a Junior/Mid-Level Data Engineer. Emphasize the importance of teamwork and effective communication in delivering successful data-driven solutions.