Data Architect - job 1 of 2

As a Data Architect at Capco Poland, your key responsibilities include designing and implementing data architecture solutions that align with business goals and technology strategies. You'll collaborate with cross-functional teams to translate data requirements into actionable designs, ensuring data integrity and security by establishing governance frameworks. Additionally, you'll mentor your team and drive the adoption of data best practices, while staying updated on emerging trends and technologies.

To qualify for the Data Architect role at Capco Poland, candidates should possess strong leadership skills, a deep understanding of data architecture principles, and effective communication abilities to convey complex concepts to diverse stakeholders. Strong consulting skills and problem-solving capabilities are essential as well, along with a solid grasp of data governance principles to enforce quality standards and protection measures.

The work culture at Capco Poland is centered around innovation, collaboration, and inclusivity. As a Data Architect, you'll be part of a flat, non-hierarchical structure that encourages direct communication with senior partners and clients. We celebrate individuality, making it essential for you to bring your authentic self to work. Our environment supports ongoing learning and development with access to various employee benefits.

Capco Poland is dedicated to the professional growth of Data Architects through continuous learning opportunities and access to a variety of business courses. We provide a platform that includes over 3,000 courses to help you acquire new skills or deepen existing ones. Furthermore, our hybrid work model allows you to balance your professional development with personal commitments effectively.

The recruitment process for the Data Architect role at Capco Poland consists of several steps: a screening call with a recruiter, a competencies interview with a hiring manager, and a final interview with clients. You’ll receive feedback and potentially an offer afterwards. This structured approach helps ensure the best fit for our team and supports a transparent hiring experience.

When designing a data architecture solution, I would start by closely collaborating with stakeholders to understand their data requirements and business objectives. My next step would involve assessing existing systems and identifying potential risks and challenges. I would then consider best practices and industry standards to design a scalable solution that ensures data integrity and security throughout the process.

In previous roles, I have implemented various data governance frameworks such as data quality management programs, access control mechanisms, and data lifecycle management procedures. I strongly believe in using a collaborative approach with all stakeholders to determine the appropriate policies and ensure compliance while enhancing data usability and trust.

To stay updated on emerging data technologies, I regularly participate in industry conferences, webinars, and online courses. Additionally, I follow key technology blogs, forums, and social media channels focused on data architecture. Engaging with a professional network of data experts also helps me to stay informed about trends and innovations in the field.

In a prior position, I faced a challenging situation with data integration from multiple sources that had inconsistent data formats. To overcome this, I redefined our data quality standards, implemented a normalization process, and collaborated with the data engineering team to ensure a seamless integration. This required persistent testing and iterative adjustments, but ultimately led to a successful and scalable solution.

Ensuring data security in architectural designs starts with defining strict access controls and encryption methods for sensitive data. Additionally, I advocate for a comprehensive data governance framework that outlines roles and responsibilities related to data protection. Regular audits and testing of security measures are crucial to identify and mitigate vulnerabilities promptly.

I encourage my team to adopt data best practices by fostering an open environment for knowledge sharing through workshops and collaborative sessions. I also emphasize the importance of continuous learning by providing access to training materials and resources. Recognizing and celebrating instances of successful implementation of best practices helps reinforce their value in our daily operations.

I have extensive experience with data modeling, particularly in creating conceptual, logical, and physical models that align with business requirements. Utilizing tools such as ERwin and Microsoft Visio, I effectively communicate modeling designs to stakeholders and ensure scalability in future developments. Collaboration with data engineers has been essential in validating these models.

Handling stakeholder communication effectively involves breaking down complex data architecture concepts into understandable terms. I make use of visual aids and analogies in presentations while actively encouraging questions to promote clarity. Building trust through transparent communication is key, and I strive to tailor my message according to the audience's technical background.

I have successfully influenced data solutions within cross-functional teams by building strong relationships and fostering open dialogue. For instance, I initiated regular alignment meetings to discuss data requirements and provide insights. By demonstrating the implications of architectural decisions on overall project success, I was able to advocate for best practices that enhanced team outputs.

Continuous improvement is integral to my work as a Data Architect. I regularly analyze our processes and outcomes to identify areas needing enhancement and remain adaptable in the face of changing technologies and business needs. Establishing feedback loops with my team allows for learning from project experiences and striving for better results in future endeavors.