Big Data Engineer (Azure)

To excel as a Big Data Engineer at Nagarro, it's crucial to have extensive experience in Azure Databricks, along with a solid background in Python, PySpark, and SQL. You should also be proficient in Azure components like Data Factory and Data Lake, and possess strong data modeling skills. Familiarity with data visualization tools and a commitment to ensuring data quality are also key attributes that can help you succeed in this role.

In your role as a Big Data Engineer at Nagarro, you will lead the technical planning for data migration and facilitate data ingestion, transformation, and storage. You'll design efficient data pipelines using Azure Databricks, develop reusable frameworks for large datasets, and ensure data integrity through validation mechanisms. Collaborating with cross-functional teams, you'll address challenges effectively while staying current with advancements in cloud computing and data engineering.

Nagarro fosters a culture of continuous learning and professional development. As a Big Data Engineer, you will have access to various resources, including training programs, workshops, and mentorship opportunities. The company encourages employees to stay up-to-date with the latest technologies, providing an environment where you can grow your skills and advance your career.

As a Big Data Engineer at Nagarro, you will engage in projects that span various industries, focusing on areas such as Supply Chain, Finance, Operations, and Customer Experience. You'll work on developing high-quality data solutions using advanced analytics and cloud technologies, helping clients overcome complex challenges and drive business growth.

Nagarro boasts a dynamic and non-hierarchical work culture. As a Big Data Engineer, you will be encouraged to collaborate with diverse teams, share insights, and actively contribute to innovative solutions. This inclusive environment promotes open communication, creativity, and teamwork, making it an exciting place to work and grow your career.

Absolutely! Nagarro offers remote work opportunities for Big Data Engineers, allowing you to maintain a healthy work-life balance while collaborating with global teams. This flexibility ensures that you can thrive both personally and professionally, contributing to meaningful projects from the comfort of your home.

A Big Data Engineer at Nagarro should be proficient in various technologies including Azure Data Factory, Azure Data Lake, Azure Databricks, Python, and PySpark. Strong knowledge of SQL is essential, along with experience in data migration, data pipeline creation, and data quality assurance processes.

When answering this question, focus on specific projects where you've designed data pipelines using Azure Databricks. Highlight how you approached challenges, the architecture you implemented, and the outcomes of those projects. This will show your practical experience and problem-solving abilities.

A good response would include the various validation and cleansing techniques you've employed in past projects. Discuss specific frameworks or processes you've implemented to ensure consistent data quality, and emphasize your attention to detail and analytical skills.

You should discuss the strategic approach you take for data migration workflows, including data ingestion, transformation, and storage solutions. Mention any specific tools or patterns you use, and how you resolve common issues that arise during migration.

Offer examples of how you've worked with product managers, data analysts, or other engineers in previous roles. Highlight your communication skills and how you ensure that all stakeholders are aligned throughout the project lifecycle.

Discuss any tools or frameworks you utilize to monitor data flow, handle errors, and optimize performance. Mention the importance of maintaining SLA agreements and how you ensure the reliability of the data solutions you deliver.

Outline your process for designing a scalable and secure data lake architecture. Consider discussing your focus on data ingestion methods, storage solutions, and security measures to protect sensitive data, and how these align with industry best practices.

Detail your proficiency with Python as it relates to data processing tasks. Provide examples of libraries you've used (such as Pandas or NumPy) and discuss specific projects that showcase your ability to write efficient data manipulation scripts.

Share a specific and detailed story about a project that encountered significant challenges, how you navigated those difficulties, and what the end results were. This showcases your problem-solving skills and resilience.

Convey your commitment to continuous learning by mentioning relevant resources you utilize such as online courses, community forums, or industry publications. You can also discuss how you implement new knowledge into your projects.

Explain your experience with PySpark in detail, highlighting how you use it for data transformation and big data processing. Provide examples of projects where PySpark was critical in achieving project objectives.