Data Architect

As a Data Architect at Intellectsoft, you will be responsible for designing the architecture for our state-of-the-art data analytics platform. This includes developing scalable data models, implementing modern data platform components like Apache Iceberg and Delta Lake, and ensuring integration of various data sources. You will also optimize data storage and retrieval, enforce data governance and compliance measures, and work closely with data scientists and engineers for seamless data usability.

To qualify for the Data Architect role at Intellectsoft, candidates should have over 7 years of experience in data architecture, engineering, and design. Strong expertise in big data technologies, knowledge of data lakes, data warehousing, and robust skills in tools like Apache Kafka, NiFi, and Spark are essential. A solid understanding of data governance, cloud services, and hands-on experience with containers and automation tools like Kubernetes and Terraform is also required.

In your role as a Data Architect at Intellectsoft, you will work with cutting-edge open-source technologies, including Apache Kafka, Spark, ClickHouse, and PostgreSQL. You will also utilize data orchestration tools like Apache Airflow, along with modern data platform components such as Apache Iceberg and Delta Lake to design and implement effective data solutions.

Intellectsoft values the growth of its employees and offers several support options for professional development. As a Data Architect, you’ll have access to Udemy courses of your choice, English courses with a native speaker, and regular soft-skills training sessions. We also organize Excellence Centers meetups and online/offline team-building events to foster collaboration and knowledge-sharing among team members.

At Intellectsoft, we prioritize work-life balance, especially for our Data Architects. You will enjoy an attractive benefit of 35 absence days per year, allowing you to recharge and maintain your well-being. This commitment to a balanced work environment ensures you can excel in your role while enjoying personal time.

A Data Architect is responsible for designing, creating, deploying and managing an organization's data architecture. This includes data modeling, ETL processes, and ensuring data security and governance measures are in place. When answering, emphasize your experience with these responsibilities and how you ensure data quality and integrity.

Discuss specific tools and technologies such as Apache Kafka, Spark, and others you've worked with. Provide examples of real-world applications and how you leveraged these technologies to solve customer problems or optimize processes. Make sure to highlight your hands-on experience.

Share your strategies for implementing data governance, including compliance with regulations like GDPR or SOC 2. Discuss how you ensure data access control and security. Provide examples of governance frameworks you've applied in previous projects.

Talk about your hands-on experience with cloud platforms such as AWS, GCP, or Azure for data storage and processing. Highlight specific projects where you utilized these services for managing large-scale data and discuss the benefits achieved.

Discuss methods you've implemented to ensure efficient data retrieval, including indexing, partitioning, and using modern solutions like Delta Lake or ClickHouse. Provide examples of improvements achieved in your past roles.

Collaboration is key in data architecture. Discuss your experience in working together with data scientists and analysts to ensure that the data architecture effectively supports their analytics needs. Describe how you gather requirements and implement solutions that facilitate their work.

Identify specific challenges, such as integrating disparate data sources or ensuring data security. Share how you approached these challenges, detailing the problem-solving techniques you employed and the outcomes of your efforts.

Express your commitment to ongoing learning by highlighting your methods, such as attending conferences, taking online courses, reading industry blogs, or participating in professional networks. Keeping current is essential in the fast-evolving field of data architecture.

Real-time data processing is crucial for many businesses. Provide examples of projects where you implemented streaming solutions using tools like Apache Kafka and how they benefited organizational decision-making.

Discuss specific data modeling techniques like Dimensional Modeling or the Inmon approach. You can provide examples of projects where these models were applied, focusing on the advantages they offered to the analytical needs of the business.