Data Engineer

A Data Engineer at MNTN is responsible for extracting and transforming data, managing ETL workflows, and generating insights to support key business decisions. You will organize data metrics and visualizations that help illustrate performance and client success.

To succeed as a Data Engineer at MNTN, you should have 2-4+ years of experience in data engineering, strong SQL expertise, hands-on experience with data warehouses, and familiarity with programming languages like Python and data processing frameworks like Spark.

Yes, the Data Engineer role at MNTN is 100% remote within the United States, making it easier for you to maintain a healthy work-life balance while contributing to an innovative company.

As a Data Engineer at MNTN, you’ll be involved in building data pipelines, managing data infrastructures, and transforming billions of data points into meaningful insights for operational improvements and client performance analytics.

Working at MNTN as a Data Engineer comes with numerous benefits, including a flexible vacation policy, annual travel expense allowance, 100% healthcare coverage, and access to coaching and professional development.

In preparing for this question, highlight any specific projects where you utilized SQL for data extraction, manipulation, and analysis. Discuss your proficiency in writing complex queries and optimizing database performance.

Provide examples of ETL processes you have designed or managed, explaining the tools you used and the impact on the data flow and accessibility for stakeholders. Focus on your understanding of data transformation and management.

Discuss your strategies for data validation, monitoring, and cleanup processes, emphasizing the importance of maintaining quality standards in data sources and reporting.

Explain your comfort level with programming languages such as Python or Java/Kotlin. Share specific situations where you've used these languages to automate data processing or enhance data pipelines.

Discuss any specific data warehouse solutions you have worked with, such as Snowflake, Redshift, or Google BigQuery, and how you utilized these tools in your data engineering projects.

Provide a situation where you identified a data issue, the steps you took to analyze and resolve it, and the outcome. Emphasize your problem-solving skills and ability to work collaboratively if necessary.

Share your understanding of the Data Engineer’s role as a critical component of an organization's data strategy, facilitating data accessibility, and enabling data-driven decision-making across departments.

Discuss your experience working with cloud services like AWS, Azure, or GCP, emphasizing any projects where you utilized cloud tools to manage data storage or enhance computation.

Discuss your approach to project management, including tools and methodologies you use to prioritize, manage deadlines, and ensure project success while balancing quality and efficiency.

Reflect on your passion for working with data and what attracted you to MNTN’s innovative culture and mission. Discuss how you envision contributing to the team’s objectives and goals.