Consultant* - Data Engineering

To be considered for the Consultant - Data Engineering position at Capco, a completed university degree is essential, along with relevant practical experience in data analytics and data science, including proficiency in machine learning and generative AI. We also value familiarity with Python libraries, such as Pandas and Scikit-Learn.

As a Consultant - Data Engineering at Capco, your primary duties will involve leading agile consulting projects focused on data in the banking and insurance industries. This includes business analysis, implementation, and building strong relationships with stakeholders while contributing innovative solutions to complex analytical challenges.

Absolutely! At Capco, we believe in fostering talent and providing multiple avenues for career advancement. As a Consultant - Data Engineering, you'll have the chance to take on leadership roles within your team and actively contribute to the growth of our Data Analytics practice.

Capco offers a range of benefits for the Consultant - Data Engineering role, including flexible working models, comprehensive onboarding, continuous professional development, health and wellness programs, and the exciting opportunity to participate in firm-wide events and clubs that enhance both personal and professional growth.

The work culture at Capco is built around authenticity and diversity, characterized by our 'Be Yourself At Work' philosophy. You'll find a collaborative environment where every individual is encouraged to bring their unique perspectives to the table, ensuring a dynamic and inclusive workplace.

Capco strongly emphasizes work-life balance. The Consultant - Data Engineering position benefits from flexible working arrangements, including hybrid work options that adapt to project demands, along with wellness initiatives and regular health checks to promote overall employee well-being.

To apply for the Consultant - Data Engineering position at Capco, simply submit your CV to our recruiting team via the provided contact email. We’re looking forward to exploring how your skills align with our innovative projects and company culture!

When addressing this question, highlight specific projects where you utilized data analytics and data science, particularly in financial services. Be sure to discuss the tools you used, the challenges you faced, and the outcomes you achieved to illustrate your experience effectively.

Prepare to discuss a project where your role was pivotal to its success. Focus on your specific contributions, how you managed stakeholders, addressed challenges, and led the team towards achieving the project objectives effectively.

It's essential to demonstrate a proactive approach to staying informed. Mention your engagement with professional communities, online courses, industry articles, seminars, and workshops, highlighting how this knowledge fuels your work and enhances your skill set.

Discuss the analytical tools and software you are familiar with, such as Python, R, Tableau, or Alteryx. Explain why you prefer these tools, touching on their functionalities, your past experiences with them, and how they support your analytical workflow.

Demonstrate your time management skills by providing a strategy for prioritizing tasks and communicating effectively with your team. Share examples of instances when you successfully met deadlines while maintaining quality.

Speak about your strategies for effective communication, understanding stakeholder needs, and establishing trust. Provide examples from your past roles where strong stakeholder relationships created positive outcomes.

This question provides a great opportunity to showcase your problem-solving abilities. Share a specific example detailing the challenge, your analytical approach, and the successful results achieved, emphasizing your role in the solution's development.

Address the importance of data quality in analytics projects by discussing your methods for validation and verification. Mention specific tools or processes you use to maintain accuracy and consistency in your data.

Provide a situation illustrating your persuasive skills. Describe the new approach, how you presented your argument, and the factors that led to gaining the stakeholders' buy-in.

Detail your familiarity with machine learning concepts, frameworks, and applications. Share specific projects where you utilized these technologies, discussing your contributions and the impacts these projects had on your organization.