Data Engineer with GCP - Local to CA or PST zone

As a Data Engineer with GCP at our company, your primary responsibilities include designing and building efficient data pipelines using GCP services like Dataproc, GCS, and BigQuery. You'll work on developing data warehouse solutions, processing large datasets, and ensuring data quality and reliability. Collaboration with other teams in an Agile environment to implement sophisticated data solutions is also essential.

To qualify for the Data Engineer with GCP role, candidates should have at least 4 years of recent experience with Google Cloud Platform and 12+ years of experience in developing data warehouse solutions. Proficiency in programming languages like Python, Java, or Scala is required, alongside familiarization with the Agile and Scrum methodologies.

In this role, the Data Engineer with GCP will utilize a variety of tools and technologies, including GCP services like Dataproc, GCS, and BigQuery. Familiarity with Hadoop, Hive, Spark, Airflow, and CI/CD tools such as Jenkins or Bamboo is also beneficial for managing extensive data processing tasks.

Currently, the Data Engineer with GCP position is onsite at our Sunnyvale, CA location. However, given the team's collaborative nature, there may be opportunities for hybrid work arrangements in the future.

The company culture is supportive, innovative, and focused on excellence. As a Data Engineer with GCP, you will join a team that values open communication, collaboration, and continuous learning. We promote a positive work environment where your contributions are recognized and encouraged.

When answering this question, highlight specific projects where you've utilized GCP. Discuss the tools you used, like BigQuery or Dataproc, and how they contributed to successful data pipeline implementations.

Share a detailed example of a data pipeline you've developed, emphasizing the technologies involved and any obstacles you encountered. This is an opportunity to showcase your problem-solving skills and technical expertise.

Discuss techniques you use for data validation, cleaning, and testing. Mention any automated frameworks you've worked with for ensuring high data quality in your delivered solutions.

Identify the languages you are most comfortable with and provide examples of projects or tasks where you've effectively used them. Emphasize any experience with Python, Scala, or Java relevant to your role as a Data Engineer.

Explain how Agile has influenced your workflow and project management style. Discuss specific methodologies like Scrum you have used and how they have benefited your team's productivity.

Share your experience with continuous integration and deployment tools, specifying which ones you've used, such as Jenkins or Bamboo, and how they've improved your development process.

Provide strategic approaches on time management and prioritizing tasks. Discuss specific tools or methods you've used to keep track of deadlines and manage workloads effectively.

Discuss specific databases you've used, whether relational or NoSQL, and share your understanding of schema design in relation to data modeling and optimization.

Describe any experience you've had with setting up or migrating to data lakes, emphasizing your understanding of various technologies and methodologies that ensure data accessibility and governance.

Use this question to express your enthusiasm for the role and how your career goals align with the company's vision. Highlight aspects of the company culture or specific projects that drew your interest.