As a Python ETL Developer at Jabil, your key responsibilities will include designing, developing, and maintaining ETL pipelines using Python and Apache Airflow. You’ll implement Data Mesh architecture, automate data workflows, and monitor pipeline performance. You'll also optimize SQL queries, collaborate with data teams, and perform data quality checks to ensure optimal operation of data services.

To qualify for the Python ETL Developer role at Jabil, candidates should have a bachelor’s degree in engineering or a related field, with 5-8 years of experience in similar roles. A strong background in Apache Airflow, SQL, PostgreSQL, and Kubernetes is essential, along with an understanding of Data Mesh principles and excellent problem-solving skills.

A Python ETL Developer at Jabil should have proficiency in Python and experience with Apache Airflow for ETL pipeline development. Familiarity with SQL, PostgreSQL, and container orchestration through Kubernetes is also required. Candidates may also benefit from knowledge of cloud platforms such as AWS or Azure, as well as monitoring tools like Prometheus and Grafana.

The work environment at Jabil for a Python ETL Developer is collaborative and innovative. You'll join a talented data engineering team, working together to tackle complex data challenges while fostering a culture of sustainability and community. The culture encourages creativity and supports continuous learning, ensuring you feel motivated and engaged.

At Jabil, Python ETL Developers have ample opportunities for growth. As you develop your skills in ETL processes, you may also explore roles in data architecture, data science, or even leadership positions within data engineering. Jabil supports career advancement through training, mentorship, and exposure to various engineering practices.

When discussing your experience with ETL processes, highlight specific projects where you've used Python and Apache Airflow. Explain your role in designing or maintaining pipelines, ensuring data quality, and any improvements you've made to enhance performance.

To answer this, discuss techniques such as indexing, query restructuring, or using aggregate functions to reduce execution time. Provide examples from past experiences where you've successfully optimized queries to improve performance.

When asked about Data Mesh architecture, explain how you apply its principles of decentralized data ownership and domain-driven design. Discuss any specific implementations you've completed and how these changes improved team collaboration and data accessibility.

Here, outline your familiarity with deploying applications on Kubernetes. Talk about specific instances where you've created deployments, managed persistent volumes, and utilized services to ensure reliable data services.

Discuss your strategies for monitoring data pipelines, such as using logging, creating alerts, or employing observability tools like Grafana. Share examples when you had to troubleshoot data issues and how you resolved them effectively.

You should emphasize the importance of establishing testing and validation processes in your ETL workflow. Mention any automated tests or checks you implement before data loads and your methods for maintaining data integrity.

Provide a specific example of a challenging data issue you've encountered. Discuss the steps you took to resolve it, what tools you used, and the impact it had on the data pipeline or project outcome.

Explain how you stay current on data engineering trends, mentioning resources such as online courses, forums, or conferences. Highlight your enthusiasm for continuous learning and improvement in your field.

Discuss your methods for effective task management, such as using project management tools or agile methodologies. Share examples of how you've successfully met deadlines while maintaining quality in your deliverables.

Emphasize the value of communication in data engineering, particularly when collaborating with data scientists and other stakeholders. Provide examples of how you've fostered effective communication to align goals and achieve successful project outcomes.