Senior Data Engineer - Octopus by RTG

The Senior Data Engineer at Octopus by RTG is responsible for designing, developing, and maintaining data pipelines and ETL processes within Cloudera and Enterprise Data Warehouse environments. Their role also includes ensuring data quality and security, troubleshooting data-related issues, and optimizing performance for analytics reporting.

Candidates applying for the Senior Data Engineer position at Octopus by RTG should have 3 to 7 years of experience in data engineering. A strong background in Cloudera, Enterprise Data Warehouse, and SQL is essential, with preference given to those who have experience in the banking sector.

The Senior Data Engineer plays a crucial role in data-driven decision-making by collaborating with business analysts and data scientists to build and optimize data pipelines. By ensuring data consistency and quality, they enable stakeholders to extract valuable insights from the data.

As a Senior Data Engineer at Octopus by RTG, you'll have the opportunity to work with cutting-edge big data technologies, particularly focusing on Cloudera, SQL databases, and data warehousing solutions, which are central to the implementation of effective data management strategies in the banking industry.

At Octopus by RTG, we highly value professional growth and development. Senior Data Engineers can expect numerous opportunities to advance their careers, work on innovative projects, and engage in continuous learning within a supportive team environment.

A great way to answer this would be to outline specific projects where you've utilized Cloudera, detailing the challenges faced and how you optimized data management or processing using its functionalities.

Explain your approach toward building data validation and cleansing mechanisms to ensure accurate data entry, as well as your experience with monitoring tools to track data discrepancies.

Discuss any techniques you've implemented such as database indexing, partitioning, and parallel processing to enhance ETL performance, giving examples from past projects.

Focus on a specific incident, describing the challenge, your approach to troubleshooting, the solution implemented, and the eventual outcome, illustrating your problem-solving skills.

Demonstrate your engagement with continuous learning through forums, courses, or professional organizations, and specify how you’ve applied any new knowledge in your work.

Discuss elements such as data accuracy, ownership, integrity, and compliance, providing examples of how you've implemented governance policies in past roles.

Highlight your experience working cross-functionally, emphasizing how collaboration with data scientists and analysts shaped project outcomes and facilitated successful data-driven insights.

Discuss your strategy for keeping clear, detailed documentation of data workflows, which will help not just you, but also other team members or stakeholders understand the processes involved.

Provide a clear narrative about the technology you had to learn, the steps you took to become proficient, and how this benefited your projects or the team.

Talk about your understanding of data vulnerabilities, compliance regulations, and your strategic outlook on implementing solutions to mitigate risks in sensitive environments.