Site Reliability Engineer - Data Lakehouse

As a Site Reliability Engineer - Data Lakehouse at ZILO, you'll be responsible for designing and maintaining scalable data pipelines, performing ETL operations to ensure data integrity, optimizing databases, and collaborating with team members to translate data requirements into solutions. Your role will also involve developing documentation on data infrastructure while staying updated with the latest technologies in data engineering.

To qualify for the Site Reliability Engineer - Data Lakehouse at ZILO, you'll need a bachelor's degree in computer science or a related field, along with a minimum of 3 years of experience in data engineering roles. Proficiency in SQL, ETL processes, and familiarity with AWS services, as well as programming knowledge in Python or Java, are essential.

The Site Reliability Engineer - Data Lakehouse supports ZILO's mission by ensuring efficient data management and analysis, which is vital for delivering a unified solution in global transfer agency. Your work will enhance operational effectiveness and drive innovation, aligning perfectly with ZILO's commitment to transforming legacy systems and putting people first.

ZILO offers an attractive benefits package for the Site Reliability Engineer - Data Lakehouse position, including 23 annual holidays, 15 public holidays, a provident fund with contributions up to 12%, health insurance that covers immediate family, and more. We value our employees and strive to create a supportive environment.

In the Site Reliability Engineer - Data Lakehouse role at ZILO, you will work with a variety of technologies, notably AWS services such as S3, Redshift, and Glue. You'll also engage with database management systems like MySQL and PostgreSQL, as well as big data technologies such as Hadoop and Spark. This variety ensures a dynamic and enriching work experience.

Absolutely! As a Site Reliability Engineer - Data Lakehouse, your role in data pipelines is to design and maintain them for efficient data processing and analysis. Highlight your experience in ETL processes and how you've ensured data integrity in your previous projects.

Discuss your hands-on experience with AWS services like S3 for storage, Redshift for data warehousing, and Glue for ETL processes. Provide examples of how you utilized these services to enhance data management.

Share your systematic approach to enforcing data quality during ETL processes, including validation checks, data cleansing methods, and monitoring systems to track the integrity of data throughout its lifecycle.

Mention your experience with various database management systems such as MySQL, PostgreSQL, or MongoDB. It's important to outline specific projects where you optimized databases or developed schema designs.

Elaborate on your programming skills, particularly in Python or Java. Talk about how you've used these languages in data engineering tasks, such as automating ETL processes or manipulating datasets.

Emphasize your ability to communicate clearly and work collaboratively with data scientists and business analysts. Provide examples of successful projects where you translated their requirements into actionable technical solutions.

Discuss your strategies for optimizing databases, including indexing, partitioning, and developing effective archiving methods. Use specific examples to illustrate the impact of your optimizations on performance.

Describe a specific data engineering challenge you faced, the approach you took to solve it, and the outcome. Focus on your analytical skills and ability to develop innovative solutions.

Highlight your experience with big data technologies such as Hadoop or Spark. If you have used these technologies in specific projects, share those details to illustrate your expertise.

Express your enthusiasm for ZILO's mission to innovate in the global transfer agency space. Speak about your desire to contribute to meaningful projects and your appreciation for their commitment to collaboration and continuous improvement.