Telstra Data Engineer Interview Questions + Guide in 2025

Telstra is Australia's leading telecommunications and technology company, known for its innovative solutions and global presence across 22 countries.

The Data Engineer role at Telstra is pivotal in designing, developing, and maintaining data pipelines and data-driven applications. This position demands expertise in technologies such as Spark, Python, and SQL, as well as familiarity with cloud platforms like Azure and AWS. The successful candidate will be responsible for ensuring data quality and security while collaborating with data scientists and business stakeholders to meet their data needs. Proficiency in building robust ETL processes, optimizing data workflows, and implementing best practices for data security is essential. Additionally, this role aligns with Telstra's values of innovation and technological advancement, as it contributes to solving significant challenges in areas like IoT, AI, and machine learning, enhancing customer experiences and operational efficiency.

This guide will help you prepare for your interview by providing a deeper understanding of the role's expectations and the skills needed to excel at Telstra.

The interview process for a Data Engineer role at Telstra is structured and designed to assess both technical and behavioral competencies. It typically consists of several stages, each focusing on different aspects of the candidate's skills and experiences.

1. Online Assessment

The first step in the interview process is an online assessment, which includes a combination of coding challenges, multiple-choice questions, and cognitive tests. Candidates are expected to demonstrate their proficiency in SQL, Python, and data structures. This assessment serves as a preliminary filter to identify candidates who possess the necessary technical skills for the role.

2. Video Interview

Following the online assessment, candidates are invited to participate in a video interview, often conducted via platforms like HireVue. This stage typically involves answering behavioral questions and may include technical questions related to past projects and experiences. Candidates should be prepared to discuss their problem-solving approaches and how they handle challenges in data engineering contexts.

3. Technical Interview

Candidates who successfully pass the video interview will move on to a technical interview. This round is usually conducted by a panel of technical experts and focuses on in-depth discussions about data engineering concepts, tools, and technologies. Expect questions related to data pipeline design, data quality assurance, and the use of technologies such as Spark, Azure, and AWS. Candidates may also be asked to solve coding problems in real-time, demonstrating their coding skills and thought processes.

4. Managerial Interview

The next step is a managerial interview, where candidates meet with a hiring manager or team lead. This round assesses the candidate's fit within the team and the organization. Questions may revolve around teamwork, leadership experiences, and how the candidate aligns with Telstra's values and culture. Candidates should be ready to discuss their career aspirations and how they can contribute to the company's goals.

5. Final Interview

In some cases, a final interview may be conducted, which could involve additional technical assessments or discussions with senior management. This stage is an opportunity for candidates to ask questions about the role, team dynamics, and the company's future direction. It also allows the interviewers to gauge the candidate's enthusiasm and commitment to the position.

Throughout the interview process, candidates should emphasize their technical expertise, problem-solving abilities, and collaborative mindset, as these are key attributes sought by Telstra.

Next, let's explore the specific interview questions that candidates have encountered during this process.

Here are some tips to help you excel in your interview.

Prepare for the Video Interview Format

Given that many candidates have reported experiences with pre-recorded video interviews, it's crucial to practice this format. Familiarize yourself with the technology and ensure you have a quiet, well-lit space for recording. Practice answering common behavioral questions in front of a camera to get comfortable with the format. Remember, you may have multiple attempts to record your answers, so take your time to present yourself confidently.

Showcase Your Technical Skills

As a Data Engineer at Telstra, you will be expected to demonstrate proficiency in SQL, Spark, and Python. Brush up on your coding skills, particularly in SQL queries and data manipulation. Prepare to discuss your experience with data pipelines, data modeling, and ETL processes. Be ready to solve coding problems on the spot, as technical assessments are a significant part of the interview process.

Understand the Company’s Data Ecosystem

Familiarize yourself with Telstra's data architecture and the technologies they use, such as Azure Data Factory, Databricks, and various data formats like Parquet and ORC. Understanding how these technologies fit into Telstra's overall strategy will help you articulate how your skills can contribute to their goals. Be prepared to discuss how you have used similar technologies in your past projects.

Emphasize Collaboration and Communication

Telstra values teamwork and collaboration, especially in Agile environments. Be ready to share examples of how you have worked with cross-functional teams, mentored junior engineers, or communicated complex technical concepts to non-technical stakeholders. Highlight your ability to adapt to changing requirements and your approach to problem-solving in collaborative settings.

Prepare for Behavioral Questions

Expect to answer behavioral questions that assess your soft skills and cultural fit. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Reflect on past experiences where you faced challenges, resolved conflicts, or contributed to team success. Tailor your answers to align with Telstra's values of innovation, customer focus, and inclusivity.

Stay Updated on Industry Trends

Given Telstra's focus on innovation in areas like IoT, AI, and machine learning, it’s beneficial to stay informed about the latest trends and technologies in data engineering. Be prepared to discuss how emerging technologies can impact Telstra's business and how you can leverage them in your role.

Ask Insightful Questions

At the end of the interview, you will likely have the opportunity to ask questions. Use this time to inquire about the team dynamics, ongoing projects, and how success is measured in the role. This not only shows your interest in the position but also helps you gauge if the company culture aligns with your values.

Be Yourself

Lastly, remember that Telstra values authenticity and diversity. Be genuine in your responses and let your personality shine through. This will help you connect with your interviewers and demonstrate that you would be a good cultural fit for the team.

By following these tips, you can approach your interview with confidence and clarity, positioning yourself as a strong candidate for the Data Engineer role at Telstra. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Telstra. The interview process will likely focus on your technical skills, problem-solving abilities, and experience with data engineering concepts and tools. Be prepared to discuss your past projects, your approach to data quality and security, and your familiarity with cloud technologies, particularly Azure and AWS.

Technical Skills

1. Can you explain the differences between ETL and ELT processes?

Understanding the nuances between these two data processing methods is crucial for a Data Engineer.

How to Answer

Discuss the definitions of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), highlighting when to use each based on data volume and processing needs.

Example

“ETL is typically used when data needs to be transformed before loading into the target system, which is common in traditional data warehousing. ELT, on the other hand, is more suitable for big data environments where raw data is loaded first and transformed later, allowing for more flexibility and speed in processing.”

2. Describe your experience with data pipeline orchestration tools. Which ones have you used?

This question assesses your familiarity with tools that automate data workflows.

How to Answer

Mention specific tools you have used, such as Azure Data Factory, Apache Airflow, or Control-M, and describe how you utilized them in your projects.

Example

“I have extensive experience using Azure Data Factory for orchestrating data pipelines. I’ve set up triggers for data ingestion from various sources, ensuring that data is processed in a timely manner while maintaining data quality.”

3. How do you ensure data quality and accuracy in your data pipelines?

Data quality is critical in data engineering roles, and interviewers want to know your strategies.

How to Answer

Discuss methods such as data validation checks, monitoring, and automated testing that you implement to maintain data integrity.

Example

“I implement data validation checks at various stages of the pipeline to catch errors early. Additionally, I use monitoring tools to track data quality metrics and set up alerts for any anomalies that may arise during processing.”

4. What is your experience with cloud data platforms, specifically Azure and AWS?

This question gauges your familiarity with cloud technologies, which are essential for modern data engineering.

How to Answer

Highlight your experience with specific services within Azure and AWS, such as Azure Databricks, AWS Lambda, or Azure Synapse Analytics.

Example

“I have worked extensively with Azure Databricks for building scalable data processing solutions. I’ve also utilized AWS Lambda for serverless data processing tasks, which has significantly reduced operational overhead.”

5. Can you describe a challenging data engineering project you worked on? What was your role?

This question allows you to showcase your problem-solving skills and experience.

How to Answer

Provide a brief overview of the project, the challenges faced, and your specific contributions to overcoming those challenges.

Example

“In a recent project, I was tasked with migrating a legacy data warehouse to Azure. The challenge was ensuring minimal downtime and data loss. I led the team in developing a phased migration strategy, which included thorough testing and validation at each stage, ultimately resulting in a successful transition.”

Behavioral Questions

1. Describe a time when you had to work with a difficult stakeholder. How did you handle it?

This question assesses your interpersonal skills and ability to manage relationships.

How to Answer

Share a specific example, focusing on your communication strategies and how you resolved the situation.

Example

“I once worked with a stakeholder who was resistant to changes in the data reporting process. I scheduled a meeting to understand their concerns and provided data-driven insights on how the changes would benefit their team. This open dialogue helped build trust and led to a successful implementation.”

2. How do you prioritize tasks when working on multiple projects?

Time management is crucial in a fast-paced environment.

How to Answer

Discuss your approach to prioritization, such as using project management tools or methodologies like Agile.

Example

“I prioritize tasks based on project deadlines and impact. I use tools like Jira to track progress and ensure that I’m focusing on high-impact tasks first. Regular check-ins with my team also help us stay aligned on priorities.”

3. Tell me about a time you had to learn a new technology quickly. How did you approach it?

This question evaluates your adaptability and willingness to learn.

How to Answer

Share a specific instance where you had to quickly get up to speed with a new technology, detailing your learning process.

Example

“When I needed to learn Azure Data Factory for a project, I dedicated time to online courses and hands-on practice. I also reached out to colleagues who had experience with the tool, which helped me gain practical insights and accelerate my learning.”

4. How do you handle stress and tight deadlines?

This question assesses your coping mechanisms in high-pressure situations.

How to Answer

Discuss your strategies for managing stress, such as time management techniques or seeking support from colleagues.

Example

“I handle stress by breaking down tasks into manageable chunks and setting realistic deadlines. I also communicate openly with my team to ensure we’re all on the same page, which helps alleviate pressure and fosters collaboration.”

5. Why do you want to work at Telstra?

This question gauges your motivation and alignment with the company’s values.

How to Answer

Express your interest in Telstra’s mission, culture, and the opportunity to work on innovative projects.

Example

“I’m excited about the opportunity to work at Telstra because of its commitment to innovation and technology. I admire how Telstra is leveraging data to enhance customer experiences, and I want to contribute to projects that have a meaningful impact on people’s lives.”