Lead Data Engineer

As a Lead Data Engineer at RKS Consulting, your primary responsibilities include designing and implementing data architectures that align with agile practices and CI/CD principles. You will also focus on cost optimization initiatives within a FinOps framework, supervising a team of data engineers, and providing essential tools for monitoring and developing solutions. In addition, you will actively engage in technological vigilance to stay updated with emerging trends in data architecture.

To qualify for the Lead Data Engineer role at RKS Consulting, candidates should possess a minimum of 5 years of relevant experience in similar projects. Proficiency in SQL, Python, and familiarity with databases like Snowflake and PostgreSQL is essential. You should also have hands-on experience with DevOps tools including Git, Docker, and Kubernetes, along with a proactive attitude toward technological advancements in data architecture.

Key technical skills for the Lead Data Engineer position at RKS Consulting include expertise in SQL and Python, as well as experience with data processing tools like DBT and Talend. Familiarity with messaging systems such as Kafka and infrastructure-as-code tools like Terraform is also beneficial. Additionally, experience with data visualization tools like Power BI will enhance your contributions to the team.

Yes, RKS Consulting allows for remote work for the Lead Data Engineer position, offering flexibility with up to two days of telecommuting per week. This allows for a balanced work-life dynamic while still engaging with exciting projects and teams effectively.

RKS Consulting values continuous learning and professional growth. As a Lead Data Engineer, you will have opportunities to engage with cutting-edge technologies and drive innovative projects. The company promotes a culture of collaboration and encourages team members to pursue ongoing education in new data architectures and methodologies, ensuring you remain at the forefront of the industry.

When answering this question, provide specific examples of data architecture designs you've implemented. Discuss the principles of agility and CI/CD you followed and share any outcomes or improvements that resulted from your designs.

In your response, explain your understanding of FinOps and how it impacts data engineering projects. Share examples of initiatives you've led or participated in that focused on improving economic efficiency through cost-saving measures.

Discuss your approach to team management, emphasizing collaboration, communication, and the tools you provide to support your team in monitoring and developing solutions. Share success stories of how you’ve empowered your team to achieve their goals.

Detail your familiarity with SQL, Python, and the various databases listed, including Snowflake and PostgreSQL. Provide examples of projects where you've successfully utilized these tools to achieve desired results.

Explain your methods for keeping current with data architecture trends, which could include attending industry conferences, following thought leaders on social media, subscribing to relevant journals, or participating in online forums.

Share a specific instance where you encountered a significant challenge in a data engineering project. Describe the problem, how you strategized to solve it, and the positive outcome that followed.

Discuss your experience with integrating DevOps tools and practices into data engineering workflows. Provide examples illustrating how you’ve enhanced deployment processes and improved collaboration between teams.

Talk about the importance of data visualization in conveying insights and facilitating decision-making. Provide examples of tools you’ve used, such as Power BI, and how they contributed to the success of your projects.

Choose a project where your technical expertise made a substantial difference. Describe what skills you applied, the project's challenges, and how your contributions led to successful results.

In your response, highlight qualities such as technical expertise, strong leadership, effective communication, and a proactive approach to problem-solving. Explain why these qualities are essential for the role and how they contribute to team and project success.