Data Engineer

As a Data Engineer at ProCook, your main responsibilities will include optimizing MySQL databases, developing and maintaining ETL pipelines, and implementing data ingestion strategies for AWS/Azure solutions. You'll also create data models that support Business Intelligence initiatives, ensuring that data is well-structured and available for analysis across the organization.

To thrive in the Data Engineer role at ProCook, candidates should have a degree in Computer Science, Data Engineering, or a related field, along with strong experience in MySQL and AWS. Advanced SQL skills, familiarity with cloud technologies, and problem-solving abilities are essential. Preferred qualifications include AWS/Azure certifications and experience with big data processing frameworks.

As a Data Engineer at ProCook, you'll have the opportunity to work with various tools and technologies including MySQL, Amazon RDS, AWS (RDS, S3, Glue, Lambda), and Azure. You'll also engage with Databricks for data integration and use monitoring tools like Prometheus and Grafana for real-time data pipeline observation.

ProCook is committed to diversity and inclusion, welcoming applications from individuals of all abilities for the Data Engineer position. They prioritize making their recruitment process inclusive and accessible, encouraging candidates to request reasonable adjustments if needed during the application or interview process.

ProCook fosters a culture of continuous learning and professional development. Data Engineers can take advantage of opportunities for training in emerging technologies, certification programs, and involvement in impactful sustainability initiatives that allow them to grow both personally and professionally within the company.

When answering this question, focus on specific MySQL projects you've worked on, including any database design and optimization tasks. Highlight your skills in query tuning and how you've ensured database performance and security.

Discuss the ETL tools you're most familiar with, such as AWS Glue or Apache NiFi, and describe how you have implemented ETL pipelines in past jobs. Provide examples of data transformations or integration processes you've successfully managed.

Be prepared to share your experience with AWS services, such as S3 and RDS, and how you've utilized these tools for data storage and management. Include specific examples of projects where you've implemented cloud-based solutions.

Explain your methods for ensuring data quality, such as implementing validation rules, data cleansing techniques, and monitoring data pipelines for anomalies. Illustrate your commitment to maintaining data integrity throughout the engineering process.

This is your chance to highlight any experience you have with frameworks like Apache Spark, Hadoop, or similar technologies. Discuss the scale of datasets you've worked with and the types of analyses you've performed.

Discuss your strategies for managing multiple priorities, such as employing project management tools, setting deadlines, and communicating with stakeholders to ensure alignment on goals and timelines.

Prepare a concrete example of a technical or project-related challenge you've encountered. Detail the steps you took to resolve the issue, the technologies you used, and the outcome of your efforts.

List the programming languages you’re proficient in, such as Python or Scala, and provide examples of how you've applied them in your data engineering projects, including any data manipulation or automation tasks.

Discuss the importance of data modeling and how you design database structures with BI needs in mind. Highlight your experience optimizing schemas to facilitate reporting and analytics.

Share your passion for data and analytics, and explain how the potential to drive decision-making and impact business performance inspires you. Discuss any personal projects or continuous learning initiatives you pursue to further your knowledge in data engineering.