Senior Data Engineer - job 1 of 2

As a Senior Data Engineer at Motive, your responsibilities include building and managing data pipelines for our enterprise products, designing data models in collaboration with product and analytics teams, and deploying advanced Data Ops methodologies. You'll be working with technologies like Airflow and AWS to improve our data processes and model effectiveness.

To qualify for the Senior Data Engineer role at Motive, candidates should possess a Bachelor's degree or higher in a quantitative field such as Computer Science, Math, or Statistics, along with at least 6 years of experience in Data Engineering. Strong skills in SQL, Python, and familiarity with modern tools like dbt and Airflow are also essential.

Motive values a collaborative and inclusive work culture, emphasizing innovation and continuous improvement. As a Senior Data Engineer, you'll be joining a diverse team that values communication and teamwork while striving for excellence in handling data challenges.

In the Senior Data Engineer position at Motive, you can expect to work with a modern data engineering stack that includes SQL, Python, Airflow, and AWS. You'll also have the opportunity to engage with data observability tools and table creation frameworks similar to dbt.

The work of a Senior Data Engineer at Motive has a significant impact, as you'll be creating data models and pipelines that directly feed products used by hundreds of thousands of users. Your expertise will help improve the efficiency and effectiveness of our operations across various industries.

When answering this question, structure your response to highlight specific projects where you designed or improved data pipelines. Discuss the technologies you used, challenges you faced, and the results of your work, emphasizing your role in enhancing the data flow and its impact on product deliveries.

In your response, discuss key principles of data model design you follow, such as normalization versus denormalization, indexing strategies, and how you evaluate scalability. Providing examples of your previous work in ensuring efficiency and scalability can demonstrate your hands-on experience.

Highlight the importance of communication and teamwork in your past experiences. You can mention specific instances where you collaborated with product or analytics teams, showcasing how you maintained clear lines of communication and worked toward shared objectives.

Use the STAR method (Situation, Task, Action, Result) to frame your story. Focus on a specific challenge, the actions you took to resolve it, and the positive results from your efforts, demonstrating problem-solving skills and resilience.

Discuss the tools you have experience with, such as Airflow, dbt, or AWS, and explain why you prefer using them based on their features, ease of use, or performance. Back your preferences with personal insights from your work experiences.

Demonstrate your commitment to continuous learning by discussing specific resources you use, such as online courses, blogs, webinars, or participation in communities. Mention how these resources have helped you in your professional growth.

Explain the approaches you take to validate data quality, such as unit testing for transformations, data profiling techniques, or integrating monitoring systems. Providing concrete examples of past experiences can enhance your response.

Describe what data observability means to you and mention tools or practices you've adopted to ensure that you gain insights into the health of your data pipelines. Emphasize that this is crucial for maintaining data integrity and trustworthiness.

Outline your experience working with AWS services relevant to data engineering, such as S3, Redshift, or Glue. Discuss specific projects you've undertaken that leveraged these services, focusing on the benefits they provided.

Convey your adaptability when faced with changing needs by sharing examples of how you've adjusted workflows or data models in response to new requirements. Highlight your emotional intelligence and ability to manage stakeholder expectations.