Data Architect

As a Data Architect at Intelliswift Software, Inc, you'll play a crucial role in designing and implementing robust data architectures to manage complex data environments. Your main responsibilities will include working with various data management tools such as Informatica and Oracle, ensuring data integrity, and transforming data into usable formats. You will collaborate with other teams to provide insights and analytics that aid in decision-making.

To qualify for the Data Architect role at Intelliswift Software, Inc, candidates should ideally have 7-10 years of experience in data warehousing and Big Data. Proficiency in Oracle, PL/SQL, and Informatica is essential, along with familiarity in technologies like XML, MQ, and shell scripting. A degree in Computer Science or a related field will also strengthen your application.

Data Architects at Intelliswift Software, Inc should possess a wide range of technical skills, including expertise in data warehousing, strong SQL knowledge, and proficiency in ETL tools like Informatica. Familiarity with systems such as Erwin, Visio, and operating systems like Unix/Linux is also important for effective data management and integration.

As a Data Architect at Intelliswift Software, Inc, you can expect to work on a variety of challenging projects that involve building and optimizing data pipelines, integrating advanced analytics, and enhancing data processing capabilities within the organization. Your contributions will directly impact the way our clients leverage their data for strategic advantages.

Absolutely! The Data Architect role at Intelliswift Software, Inc not only offers competitive pay but also provides numerous growth opportunities within the company. You'll have the chance to tackle diverse projects and expand your skillset, with support from senior management. This role is ideal for individuals looking to develop their careers in data architecture and related fields.

In answering this question, you should highlight specific projects you've worked on involving data warehousing techniques, the tools you have used, and the outcomes of those projects. Make sure to touch on the processes you followed and how your role contributed to the success of the project.

Discuss your strategies for gathering requirements, assessing existing data sources, and ensuring scalability and efficiency in your design. It's important to emphasize your step-by-step approach and highlight any relevant experiences that showcase your analytical thinking and problem-solving skills.

Describe your hands-on experiences with ETL tools like Informatica, focusing on specific tasks you've accomplished with them. You could elaborate on how you've optimized ETL processes or addressed challenges in data integration workflows, illustrating your technical skills.

Ensure to mention any data validation techniques you've employed, as well as your experience in conducting data audits. Discuss your awareness of best practices in data governance and how these contribute to maintaining high standards of data quality.

Share specific instances where you have utilized cloud platforms or services for data architecture, such as AWS or Azure. Talk about how these platforms impacted your projects and the advantages they offered over traditional infrastructures.

Mention any professional development activities you participate in, such as webinars, online courses, or industry conferences. Emphasize the importance of continuous learning and networking in keeping your skills and knowledge relevant in this fast-evolving field.

When answering this, refer to a specific challenge, outline your approach to resolving it, and highlight the outcomes. This not only shows your problem-solving abilities but also your capacity to remain calm under pressure.

Discuss the various data modeling techniques you've implemented, such as entity-relationship diagrams or dimensional modeling, and how they have contributed to successful data projects. Provide examples where possible.

Share your approach to simplifying technical jargon and using visuals or analogies to help stakeholders grasp complex concepts. Emphasize the importance of effective communication in ensuring project buy-in from all parties.

Talk about how a Data Architect collaborates with cross-functional teams, providing guidance and leadership on data strategies. Highlight the value of teamwork in delivering successful data solutions and how you can contribute in this capacity.