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Senior Data Engineer

Our Company:

QiH is a fast-growing, innovative, and progressive scale-up business headquartered in London with a collective of brilliant brains in Skopje. We are at the start of an exciting journey as we build out our internal engineering capability, spearheading our tech transformation, building best in class products and tackling exciting and complex challenges along the way!

Data is at the core of what we do at QiH, but our people are at the heart of our success! At QiH, we have created an energetic and target-driven culture and continuously invest in each individual.

The Role

Our Technology team is growing! We’re looking for a highly skilled and experienced Senior Data Engineer to design and build a robust, scalable, and high-performance real-time data backbone. 

In this role you will lead the design, development, and implementation of a real-time data backbone. This position focuses on building and maintaining scalable, high-performance data pipelines that support real-time data processing and analytics. You will work closely with various teams to ensure the infrastructure meets the business's growing data needs while leveraging modern technologies for efficient data ingestion, storage, and analysis..

Key Responsibilities:

  • Design, develop, and maintain scalable real-time data pipelines and infrastructure.

  • Integrate various data sources and ensure seamless real-time data flow across the organisation.

  • Build efficient, fault-tolerant, and highly available data ingestion processes.

  • Monitor and improve data pipeline performance and scalability for low-latency and high-throughput.

  • Work closely with cross-functional teams, including software engineers, data scientists, and business stakeholders, to ensure data infrastructure aligns with business objectives.

About You:

  • Hands-on experience in data engineering with a proven track record of building and managing real-time data pipelines across a track record of multiple initiatives.

  • Expertise in developing data backbones using distributed streaming platforms (Kafka, Spark Streaming, Flink, etc.).

  • Experience working with cloud platforms such as AWS, GCP, or Azure for real-time data ingestion and storage.

  • Programming skills in Python, Java, Scala, or a similar language.

  • Proficiency in database technologies (SQL, NoSQL, time-series databases) and data modelling.

  • Strong understanding of data pipeline orchestration tools (e.g., Apache Airflow, Kubernetes).

  • You thrive when working as part of a team

  • Comfortable in a fast-paced environment

  • Have excellent written and verbal English skills

  • Last but not least, you’ll have no ego!

What You’ll Get:

  • Competitive Basic Salary 

  • Quarterly Bonuses

  • Hybrid working

  • Private Health Care (Bupa)

  • Market Leading Training Programme

  • Recognition & Reward Scheme

  • Annual Company Conference (previous destinations Bologna, Dubrovnik, Belgrade and Thessaloniki)

  • Regular Happy Hour / Team Lunches

  • Free Coffee, Drinks & Snacks

What’s the next step?

Our hiring process ensures we're recruiting the right people for the role. We ensure that people are as suitable for us as we are for them.

If you like the sound of what we're all about at QiH and want to join a team where you can make an impact, please apply or contact us at careers@qih-group.com.

Average salary estimate

$75000 / YEARLY (est.)
min
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$60000K
$90000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Data Engineer, QiH Group

At QiH, a dynamic scale-up based in London, we're on an exciting mission to enhance our internal engineering prowess and craft extraordinary products that tackle complex challenges head-on. Our Senior Data Engineer position is pivotal to this journey. In this role, you'll lead the design and implementation of our real-time data backbone, ensuring that we have a robust and scalable infrastructure to meet our growing data needs. You'll collaborate with talented teams across the company, integrating various data sources for seamless data flow and maintaining high-performance data pipelines. If you have hands-on experience building data pipelines using distributed streaming platforms like Kafka, Spark, or Flink, and are proficient in cloud platforms such as AWS or Azure, you could be the perfect fit! Your programming skills in Python or Java, along with expertise in SQL or NoSQL databases, will play a crucial role in our tech transformation. At QiH, we value our people as much as our data, fostering an energetic culture where continuous investment in each individual is more than a motto; it’s our practice. With competitive salaries, quarterly bonuses, and a focus on professional development, you'll find a rewarding environment where you can thrive and make a tangible impact!

Frequently Asked Questions (FAQs) for Senior Data Engineer Role at QiH Group
What are the responsibilities of a Senior Data Engineer at QiH?

A Senior Data Engineer at QiH is responsible for designing, developing, and maintaining scalable real-time data pipelines. This role includes integrating various data sources, ensuring the seamless flow of data throughout the organization, and building fault-tolerant ingestion processes. The engineer will also monitor and enhance pipeline performance and collaborate with cross-functional teams to align data infrastructure with business objectives.

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What qualifications are required for the Senior Data Engineer position at QiH?

To qualify for the Senior Data Engineer role at QiH, candidates must have hands-on experience in data engineering, particularly building and managing real-time data pipelines. Expertise in distributed streaming platforms like Kafka or Spark, proficiency in cloud platforms (AWS, GCP, or Azure), and strong programming skills in Python, Java, or Scala are essential. Additionally, a solid understanding of database technologies and data pipeline orchestration tools is required.

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What technical skills should a Senior Data Engineer have to succeed at QiH?

A successful Senior Data Engineer at QiH should possess technical skills in distributed streaming platforms such as Kafka and Spark Streaming, as well as programming language proficiency in Python, Java, or Scala. Familiarity with cloud storage solutions (AWS, GCP, Azure) and knowledge of SQL and NoSQL databases are also vital, along with experience in pipeline orchestration tools like Apache Airflow or Kubernetes.

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What kind of projects will a Senior Data Engineer work on at QiH?

At QiH, a Senior Data Engineer will work on projects focusing on building robust, high-performance data pipelines that support real-time data processing and analytics. This includes integrating diverse data sources to ensure efficient data flow, improving pipeline performance, and collaborating with other teams to ensure alignment with business goals.

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What is the company culture like at QiH for a Senior Data Engineer?

The company culture at QiH is energetic, target-driven, and collaborative, emphasizing the importance of both individual contributions and teamwork. As a Senior Data Engineer, you'll thrive in a fast-paced environment, have opportunities for professional development, and be part of a supportive team that values its members and encourages innovation and growth.

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Common Interview Questions for Senior Data Engineer
What experience do you have with building real-time data pipelines?

Discuss specific projects where you've designed or implemented real-time data pipelines, detailing the technologies you used, the challenges you encountered, and the impact of your work. Be sure to highlight experience with distributed streaming platforms and how you ensured pipeline performance.

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How do you ensure data quality in your pipelines?

Emphasize your strategies for maintaining data integrity and quality within your pipelines, such as implementing validation processes, monitoring data flow, and using error-handling frameworks. Providing specific examples of how you've handled data discrepancies can be very effective.

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Which cloud platforms have you worked with, and what were your contributions?

Share your experience with specific cloud platforms like AWS, GCP, or Azure, detailing what services you used for data ingestion and storage. Highlight any architectures you designed and how they contributed to workflow efficiency, scalability, or cost savings.

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Can you explain the significance of orchestration tools like Apache Airflow?

Talk about the role of orchestration tools in managing data pipeline workflows, detailing how Apache Airflow helps in scheduling, monitoring, and maintaining the workflows you’ve built. Describe any significant improvements you achieved due to implementing such tools.

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Describe a time when you had to troubleshoot a data pipeline failure.

Provide an example scenario, focusing on the steps you took to diagnose the problem, the tools you used for troubleshooting, and how you resolved the issue. Highlight your analytical skills and the importance of maintaining smooth data flow.

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How do you approach collaboration with cross-functional teams?

Emphasize your communication skills and your methods for ensuring effective collaboration, such as setting up regular meetings, using collaboration tools, or creating shared documentation. Share experiences that demonstrate your ability to work well with software engineers, data scientists, and business stakeholders.

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What programming languages do you prefer and why?

Discuss your proficient programming languages such as Python, Java, or Scala, and explain why you prefer using them for data engineering tasks. Include specific features or libraries that make these languages a good fit for building data pipelines.

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How do you manage scalability in your data infrastructure?

Highlight your understanding of scalability issues and your experience in designing systems that can grow effectively. Discuss architecture patterns, technologies used, and any scaling challenges you've overcome.

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What motivated you to apply for the Senior Data Engineer position at QiH?

Share your enthusiasm for QiH’s mission and culture. Discuss how your background aligns with the role, and express your desire to contribute to exciting projects and make an impact in a team that values innovation and collaboration.

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What trends do you foresee shaping the future of data engineering?

Demonstrate your interest in the field by discussing current trends such as the rise of real-time processing, the integration of AI in data engineering, or advancements in data governance. Express your eagerness to adapt and leverage these trends in your work.

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Full-time, hybrid
DATE POSTED
April 2, 2025

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