RAID Developer

As a RAID Developer at Advansys, your primary responsibilities include developing and maintaining SQL-based solutions, designing scalable data processing systems with Apache Spark and Hive DB, and optimizing data pipelines using Python. You will also collaborate closely with data teams to turn business requirements into actionable technical solutions.

To excel as a RAID Developer at Advansys, you should have strong skills in SQL and PL/SQL, extensive experience with Hive DB, proficiency in Apache Spark, and a solid understanding of Python programming. Familiarity with data warehousing concepts, big data technologies, and Linux is also beneficial.

At Advansys, the work culture for a RAID Developer is collaborative and supportive. You will work alongside a diverse team of skilled professionals who prioritize innovation and teamwork, ensuring you have the resources you need to succeed in developing impactful data solutions.

Yes! Advansys offers considerable opportunities for career growth for RAID Developers. With a focus on continuous learning and skill enhancement, you can expand your expertise and explore new roles as you contribute to various projects within the company.

Advansys ensures data system performance by monitoring and optimizing the efficiency of SQL queries, PL/SQL procedures, and Spark jobs. RAID Developers actively implement best practices for code quality, security, and testing to handle data growth and maintain system scalability.

In answering this question, highlight specific SQL queries or PL/SQL procedures you've developed, focusing on how they improved efficiency or solved a particular problem in previous projects.

Discuss your approach to building and optimizing data pipelines using Python, including any libraries or tools you utilized and the measurable outcomes such as reduced processing times or improved accuracy.

Share specific troubleshooting strategies you've employed in past projects, such as analyzing query execution plans, utilizing SQL profilers, or using logging tools to pinpoint performance bottlenecks.

Provide examples of how you've utilized Apache Spark in large-scale data processing, such as specific Spark jobs you implemented, the size of the datasets handled, and the impact on performance.

Elaborate on your collaborative experiences with data scientists and analysts, emphasizing how teamwork has facilitated better project outcomes and how you communicate technical concepts effectively.

Be prepared to discuss a specific complex SQL query you've crafted. Explain the challenge it addressed, the logic behind your approach, and any optimizations you implemented to enhance performance.

Describe your familiarity with data warehousing, including specific architectures you’ve used, the tools involved, and how they relate to the data systems you’ve built.

Outline your practices around code reviews, testing protocols, and any tools you use for maintaining security and quality in your data systems, citing particular examples when possible.

Discuss a specific challenge in a data integration project, illustrating your problem-solving approach. Mention tools or methodologies that helped you overcome that challenge effectively.

Identify any additional big data technologies you've worked with, like Hadoop or Kafka, and elaborate on your experiences and how they complement your role as a RAID Developer.