At a Glance
- Tasks: Build and optimise data pipelines while collaborating with diverse teams.
- Company: Betty, a pioneering entertainment company in online gaming.
- Benefits: Career development, fun team culture, and a modern office space.
- Other info: Exciting opportunities for growth in a dynamic industry.
- Why this job: Join us to redefine online gaming with innovative data solutions.
- Qualifications: 3+ years in data engineering, strong Python and SQL skills.
The predicted salary is between 60000 - 80000 £ per year.
Betty is an innovative entertainment company pioneering at the intersection of real money online casino and casual mobile gaming. Accredited by the Alcohol and Gaming Commission of Ontario (AGCO) as a B2C operator in February 2023, we've set a new standard in the industry. Our mission is to redefine the online casino experience by offering a uniquely transparent environment where players can relax, unwind, and enjoy themselves safely. We are committed to accessibility, fairness, and inclusivity, fostering a community of like‑minded individuals who value ethical gaming practices and prioritize our players' safety and enjoyment above everything else.
Key Responsibilities
- Collaborate with cross‑functional teams, including Engineering, and business stakeholders, to define and understand data requirements.
- Develop and maintain scalable data pipelines for loading data from different sources into the DWH.
- Optimize and fine‑tune existing data processes for improved performance.
- Collaborate with infrastructure teams to implement scalable and secure data platform.
- Create and maintain reports for regulatory requirements and internal business needs.
- Evaluate and implement new technologies, tools, and frameworks to enhance data processing and storage capabilities.
Requirements
- Bachelor's degree in Computer Science, Data Science, or a related field.
- 3+ years of experience in a data warehouse engineering or related role.
- Experience with cloud data warehousing technologies, such as Amazon Redshift, Snowflake, or Google BigQuery.
- Good programming skills in Python.
- Proficiency with SQL and data modelling.
- Experience with pipeline orchestration tools (e.g., Airflow, Dagster).
- Understanding of CI/CD principles and experience implementing automated deployment processes.
- Excellent analytical and problem‑solving skills.
- Strong communication and teamwork skills.
- Fluency in English.
Nice to have
- Experience with DBT.
- Experience with stream processing frameworks (e.g., Apache Kafka).
- Experience with containerization technologies (Docker, Kubernetes).
- Experience with data visualization tools (e.g., Looker, Tableau, Power BI).
What we offer
- Career and skills development opportunities.
- Fun and collaborative team environment.
- New modern office space.
Senior Data Engineer London, UK employer: betty.ca
At Betty, we pride ourselves on being an exceptional employer, offering a vibrant and inclusive work culture that champions innovation and collaboration. Our London office provides a modern workspace where creativity thrives, alongside ample opportunities for career growth and skills development in the rapidly evolving gaming industry. Join us to be part of a team that values ethical practices and prioritises employee well-being, all while redefining the online casino experience.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer London, UK
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We think you need these skills to ace Senior Data Engineer London, UK
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at betty.ca
✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
