Data Engineer

To apply for the Data Engineer position at ComeOn Group, you should ideally have a degree in a quantitative discipline like computer science or mathematics, alongside at least three years of extensive experience in data integration, real-time streaming, or data warehousing. Proficiency in programming languages like Scala or Java and experience with big data technologies such as Spark, Flink, or Kafka are key qualifications.

As a Data Engineer at ComeOn Group, your responsibilities will include the design, build, and maintenance of robust data pipelines and ensuring data quality through best practices. You will troubleshoot data feed issues and work with various teams across the organization, from analysis to release, to ensure all regulatory reporting data flows smoothly through our systems.

Data Engineers at ComeOn Group will enjoy a collaborative yet dynamic work environment that emphasizes flexibility. With a hybrid work model, you can work from home or in our vibrant office space designed to foster both focused work and creative exchanges, promoting teamwork and innovation in the iGaming industry.

At ComeOn Group, Data Engineers can expect an attractive remuneration package that includes a company bonus scheme, flexible remote work options, and up to 40 days per year to work fully remotely. Other perks include a one-time workstation setup bonus, office meals, team events, and a well-being allowance.

For the Data Engineer role at ComeOn Group, familiarity with AWS or GCP environments for cloud data processing is important, alongside experience with big data technologies such as Spark, Flink, Kafka, and SQL query writing. Knowledge of data warehousing principles and tools like Airflow would be advantageous.

To learn more about the company culture at ComeOn Group, you can visit our website or explore our social media channels where we regularly share insights and updates. Engaging with our content on platforms like LinkedIn, Instagram, and Facebook will provide a deeper dive into our vibrant work culture and values.

Absolutely! As a Data Engineer at ComeOn Group, you will find significant room for growth and professional development. With ongoing challenges and learning opportunities in the expanding iGaming space, you will have the chance to enhance your skills and take on new responsibilities as you build the framework for our regulatory data processes.

In your response, highlight specific examples where you successfully integrated data from various sources or managed real-time streaming data. Discuss the tools you used, such as Apache Kafka or Spark, and outline how your approach ensured data quality and maintained performance under load.

To answer this, share your strategies for maintaining data quality, such as implementing rigorous testing, validation processes, and monitoring systems. Discuss any tools or frameworks you've used to automate these processes and the impact they had on successfully delivering accurate data solutions.

Illustrate a specific instance of a complex data challenge, detail the steps you took to identify the root cause, and explain how you collaborated with your team to implement a solution. This demonstrates your problem-solving abilities and effective communication in high-pressure situations.

Be specific about the programming languages you excel in, such as Scala or Java, and provide examples of projects or tasks where you've applied them in building data pipelines or performing data transformations. Discuss your familiarity with libraries or frameworks relevant to those languages.

Discuss any tools you've used for data orchestration, like Apache Airflow, and elaborate on how you implemented workflows to automate data pipeline processes. Highlight the efficiency improvements and reliability gains achieved through your orchestration strategies.

In your answer, emphasize your commitment to continuous learning by mentioning online courses, industry publications, and networking with peers. You can also discuss specific technologies or trends you're currently exploring or implementing in your work.

Describe your proficiency with various cloud services, including specific services within AWS and GCP that you've utilized for data engineering tasks. Provide examples of how you leveraged cloud solutions to optimize data processing and storage capabilities for large datasets.

In this response, discuss your approach to task prioritization, whether through project management tools, agile methodologies, or personal organization techniques. Highlight how effective prioritization led to timely project completion without sacrificing quality.

Talk about any data warehousing solutions you’ve implemented or worked with, such as Snowflake or Amazon Redshift. Discuss the architecture of the solutions and how they facilitated data accessibility and reporting across different business units.

Express your vision of the future of data engineering in the iGaming sector, emphasizing its critical role in regulatory compliance, player experience enhancement, and data-driven decision-making. Discuss emerging trends you anticipate and how they will impact the industry.