Data Platform Engineer

Data Platform Engineer

Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
T

At a Glance

  • Tasks: Ensure reliable data pipelines and collaborate with teams to enhance operational efficiency.
  • Company: Leading iGaming company focused on innovative gaming experiences.
  • Benefits: 26 days paid holiday, private medical insurance, and a supportive team environment.
  • Other info: Opportunities for personal growth and a collaborative work culture.
  • Why this job: Join a dynamic team and make a real impact in the iGaming industry.
  • Qualifications: 2+ years in Data Ops or similar role, strong SQL and Python skills.

The predicted salary is between 60000 - 80000 £ per year.

Team Creation is a leading iGaming company dedicated to delivering innovative and exciting gaming experiences to players worldwide. We pride ourselves on our commitment to excellence, integrity, and customer satisfaction.

Role Overview: Team Creation is a leading iGaming development company in the Asia market. We are looking for a highly motivated DataOps Engineer to join our Data team. In this role, you will be responsible for ensuring the stability, reliability, and quality of our data pipelines and internal data systems. You will work closely with Data Engineers, IT Infrastructure, IT Operations, and Data Analysts/Scientists to maintain data workflows, improve operational efficiency, and ensure data is delivered accurately and on time. This role is critical to sustaining data freshness, pipeline robustness, platform observability, and smooth operations across multiple products and internal backend tools.

Key Responsibilities:

  • Ensure the reliable and timely execution of daily data pipelines and scheduled workflows.
  • Operate and maintain internal data services, including ingestion layers, OLAP/lake storage, materialised views, and task dependencies.
  • Contribute to CI/CD workflows for data pipelines and participate in deployments, version management, and change control.
  • Monitor orchestration systems (e.g., Airflow), troubleshoot pipeline failures, delays, and anomalies, and drive continuous performance improvements.
  • Implement and maintain data quality checks, anomaly detection, schema validation, and audit processes.
  • Collaborate with Data Engineers on table lifecycle management, storage optimisation, partitioning strategies, and schema evolution.
  • Work with IT Infrastructure and IT Operations teams to improve platform observability, including logging, metrics, and alerting.
  • Develop and maintain SOPs, platform standards, best practices, and troubleshooting documentation.
  • Provide operational support to internal users (DE/DA/DS/Ops) for issues such as query performance, missing data, or inconsistent KPIs.

Requirements & Skills:

  • 2+ years of experience in Data Ops, Data Engineering, BI Engineering, or a similar operational data role.
  • Experience with CI/CD workflows, Docker, Kubernetes, or other DevOps-related practices.
  • Hands-on experience with workflow orchestration tools such as Airflow (or equivalent).
  • Familiarity with mainstream data engineering technologies such as Kafka, Spark, Flink, Delta Lake, Iceberg, Hudi, ClickHouse, or Doris.
  • Good understanding of data warehousing concepts, including partitioning, schema evolution, table lifecycle management, and OLAP vs. data lake architectures.
  • Strong SQL skills and familiarity with Python for scripting, automation, or validation.
  • Strong debugging and problem-solving skills, especially for data anomalies and pipeline failures.
  • Comfortable working cross-functionally with DE/Infra/Ops/DA/DS teams in a fast-paced environment.
  • Mandarin proficiency is preferred.

Preferred Qualifications:

  • Experience supporting data operations for back-office systems, risk management workflows, or internal platform tools.
  • Familiarity with monitoring and alerting tools (e.g., Prometheus, Grafana, ELK).
  • Knowledge of cloud platforms (AWS, GCP, or Azure).
  • Exposure to ML pipelines or model-serving infrastructure is a plus.

We Offer:

  • Experience a dynamic and team-orientated work environment.
  • Opportunities for personal growth and learning.
  • An open, inclusive and supportive team where you will be valued, and your suggestions will be welcome.
  • 26 days paid holiday per year, in addition to local public holidays.
  • Risk Benefits such as pension, Life Assurance (4x annual salary), Private Medical Insurance.

Data Platform Engineer employer: Team Creation

At Team Creation, we foster a dynamic and collaborative work environment that prioritises innovation and personal growth. As a Data Platform Engineer, you will be part of a supportive team that values your contributions and encourages continuous learning, all while enjoying competitive benefits such as 26 days of paid holiday and comprehensive risk benefits. Join us in the vibrant Asia market and help shape the future of iGaming with your expertise in data operations.

T

Contact Details:

Team Creation Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Platform Engineer

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Team Creation!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Platform Engineer at Team Creation.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Team Creation.

Apply Directly through Our Website

When you find a suitable opening like Data Platform Engineer at Team Creation, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Platform Engineer

SQL
Python
Data Pipeline Development
Automation
Data Engineering
API Integration
Problem-Solving Skills

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Team Creation, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Team Creation. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Team Creation

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Team Creation!

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.