Data Engineer II

As a Data Engineer II at PriceSpider, your primary responsibilities include designing and deploying complex data engineering solutions, managing data pipelines, and ensuring data integrity across our systems. You will work with tools like Snowflake and BigQuery, analyze software systems, and collaborate with cross-functional teams to improve our data architecture.

To apply for the Data Engineer II role at PriceSpider, candidates should have a BS degree in Computer Science or a related field, alongside strong experience with OLAP data environments such as BigQuery or Snowflake. Candidates should also possess advanced SQL skills, and experience with data mining and processing large volumes of data.

PriceSpider is committed to the growth of its employees, particularly in the Data Engineer II role. We offer professional development programs aimed at enhancing your technical skills and knowledge. This includes access to resources, training, and opportunities for continuous learning.

In the Data Engineer II position at PriceSpider, you will be working with advanced data analytics and cloud platforms like Snowflake, BigQuery, and Looker. You'll also use various programming languages such as Python and SQL for data processing, transformation, and integration.

At PriceSpider, the work culture is vibrant and supports a strong work-life balance. We prioritize inclusion and diversity, where ideas are encouraged and every talent is valued. As a Data Engineer II, you will find a collaborative environment that promotes rapid iteration and agile methodologies.

When answering this question, emphasize specific projects where you designed and implemented data pipelines. Describe the technologies you used, the challenges faced, and the impact your work had on data accessibility and reliability.

Discuss your approach to monitoring data quality, including the tools and methodologies you use. Mention any specific frameworks you've implemented for data cleaning and validation while highlighting your commitment to maintaining data integrity.

Explain your understanding of SQL performance tuning techniques. Talk about your experience with indexing, query restructuring, and using EXPLAIN plans to optimize SQL queries and enhance performance in data retrieval.

Provide examples of your experience working with big-data tools such as Hadoop or Spark, focusing on specific use cases where you processed terabytes of data, along with the methods you used to streamline data handling.

Emphasize your communication skills and willingness to work with teams from different departments. Discuss experiences where collaboration led to significant improvements in project outcomes or efficiency.

Share a specific example of a complex data challenge, the steps you took to tackle the issue, and the results. Highlight how your analytical skills and technical knowledge were fundamental in finding a solution.

Detail the programming languages you're experienced with, such as Python, Go, or Java. Provide examples of how you've used these languages in data engineering projects and the types of problems they helped you solve.

Discuss your time management strategies, such as prioritization techniques and tools you use for project tracking. Explain how you maintain quality while meeting tight deadlines.

Describe your familiarity with cloud technologies like AWS or Google Cloud. Talk about specific projects where you've utilized cloud platforms to enhance data storage, processing capabilities, or scalability.

Share your strategies for professional growth, including following industry blogs, attending workshops, and participating in online courses. Demonstrating a commitment to staying up-to-date shows your passion for the field.