Data Engineer (Azure)

As a Data Engineer at our company, your main responsibilities include developing and operating our Azure data platform, particularly in Data Warehousing and data integration. You'll design and create ETL/ELT processes, optimize load processes across the data pipeline, and ensure quality data handling. Collaborating closely with stakeholders and documenting data flows while contributing to data quality and governance standards are also key parts of your role.

To become a Data Engineer at our company, candidates should have solid experience in data integration and processing, specifically with Data Warehouses or modern data architectures such as Lakehouse. Proficiency in languages and tools like T-SQL, Python, and Azure Data Factory, along with knowledge of data formats such as Parquet, CSV, and JSON, is essential. Strong communication skills and the ability to work in a collaborative environment are also critical for this role.

Data Engineers at our company mainly utilize Azure's data platform, incorporating tools such as Azure Data Factory for ETL/ELT processes, T-SQL for queries, and Python for scripting. Familiarity with data formats such as Parquet, CSV, and JSON is required. Knowledge of additional technologies like Spark and artificial intelligence can be advantageous.

Yes, experience in the banking sector can be a significant advantage for a Data Engineer role at our company. Understanding financial data and business processes can enhance your contributions to developing solutions that are not only efficient but also align with industry standards.

Soft skills are essential for a Data Engineer at our company. Strong communication abilities are crucial for collaboration with both internal and external stakeholders. Additionally, having a proactive approach and being willing to engage in designing processes in a family-oriented, sustainable work environment will help you succeed in this role.

When answering this question, discuss specific ETL/ELT projects you've worked on, the tools you used, and the challenges you faced. Use examples from your past experience to illustrate your problem-solving capabilities and successful outcomes.

Explain the methodologies you follow for data modeling, such as star or snowflake schemas. Discuss how you've translated business requirements into data models and include examples of any BI projects where your models improved reporting and analytics.

Discuss strategies you employ to maintain data quality, such as validation processes or automated testing of data flows. Mention any tools or frameworks you've used to monitor and optimize data pipelines.

Provide details about specific projects where you've used Azure Data Factory. Highlight key functionalities you've used, such as creating and managing pipelines, working with different data sources, and automating workflows.

Discuss a specific instance where you encountered difficulties in loading data. Explain the steps you took to identify the root cause and how you implemented solutions that benefitted the overall data pipeline.

Share your approach to documenting data flows, such as using visual tools or code documentation best practices. Emphasize the importance of these documents in team collaboration and data governance adherence.

Talk about your experience handling different types of data, the tools you use for each format, and how you convert between them. Include examples that illustrate your ability to manage complexity in data processing.

Demonstrate your commitment to continuous learning by discussing relevant courses, webinars, or conferences you attend. Mention any specific areas of technology or practices you are particularly excited about.

Provide an example that showcases your communication skills and ability to explain technical concepts to non-technical audiences. Highlight the importance of understanding their needs and how that led to successful project outcomes.

Personalize your response by discussing your alignment with the company’s mission and values. Highlight what excites you about working in this team and how your skills and experiences match the Data Engineer position.