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For Companies At a Glance
- Tasks: Design and maintain scalable data pipelines for analytics and reporting.
- Company: Join a dynamic team in a leading corporate environment.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Make an impact by transforming raw data into valuable insights.
- Qualifications: 2+ years in Data Engineering, strong SQL skills, and programming experience.
- Other info: Collaborative culture with a focus on innovation and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for a skilled and experienced Data Engineer to join our Data team. In this role, you will design, build and maintain scalable data pipelines and robust data models to support analytics, reporting, operational workflows, back-office and risk systems, and product data needs. You will work closely with Data Analysts / Data Scientists, and Business stakeholders to provide clean, reliable, and high-quality data that supports data-driven decisions.
You’ll be responsible for turning raw data from multiple sources into well-structured, analysis-ready datasets, and building the backbone of our data platform to meet both current and future business demands.
Key Responsibilities- Design, implement and maintain scalable, robust data pipelines (batch and streaming) for ingestion, transformation, and integration of data from diverse internal systems.
- Build and maintain data models, schemas, and data tables (warehouse/lakehouse) that support analytics, reporting, and operational workloads.
- Develop ETL/ELT workflows, transformation logic, aggregation and enrichment logic to produce clean, high-quality, analysis-ready datasets.
- Collaborate with Data Analysts, Data Scientists, and Business stakeholders to gather requirements, translate them into data specifications and data structures.
- Optimize data storage and processing performance: manage partitioning, indexing, schema design, table layout, resource allocation for efficient processing and query performance.
- Maintain and document data architecture, source-to-target mappings, lineage definitions, and schema versions; ensure clarity and maintainability of data assets.
- Ensure data quality, consistency and reliability so downstream analytics, reporting and operations teams can trust the data.
- 2+ years of experience in Data Engineering or similar data-intensive engineering role.
- Strong proficiency in SQL and at least one programming language (e.g. Python).
- Hands-on experience with batch and streaming data processing, using frameworks such as Spark, Flink, or similar distributed processing frameworks.
- Familiarity with modern data lakehouse or data warehouse technologies, such as Delta Lake, Apache Hudi, ClickHouse, Doris.
- Strong understanding of data modelling principles, schema design, partitioning strategy, data, and data architecture patterns.
- Proven skills in writing clean, maintainable, and well-documented data transformation code; ability to design pipelines that are robust, testable, and scalable.
- Ability to communicate effectively with both technical and non-technical stakeholders and translate business requirements into technical data solutions.
- Good problem-solving ability, attention to detail, and ability to troubleshoot complex data issues and performance bottlenecks.
- Mandarin proficiency is preferred.
- Experience with containerization or infrastructure tooling (e.g. Docker, Kubernetes), or involvement in CI/CD workflows.
- Experience working on large-scale data systems, high-volume data ingestion, distributed storage, and analytical workloads.
- Exposure to supporting machine learning pipelines or data science workflows.
- Familiarity with cloud concepts is a plus.
Data Engineer (Chinese Speaking) Corporate · Hammersmith · employer: Eeze Entertainment Malta Limited
Contact Detail:
Eeze Entertainment Malta Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Chinese Speaking) Corporate · Hammersmith ·
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who might know about openings at companies you're interested in. A friendly chat can sometimes lead to a referral, which is a golden ticket in the job hunt.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, whether it's a GitHub repo or a personal website. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the company’s data needs. Practice common data engineering questions and be ready to discuss how your experience aligns with their requirements.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team!
We think you need these skills to ace Data Engineer (Chinese Speaking) Corporate · Hammersmith ·
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, SQL, and any relevant programming languages like Python. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include any projects or experiences that demonstrate your ability to build and maintain data models or pipelines. If you've worked with frameworks like Spark or Flink, let us know! Real-world examples can really make your application stand out.
Be Clear and Concise: When writing your cover letter, be clear about why you want to join StudySmarter and how you can contribute to our data team. Keep it concise but informative – we appreciate a straightforward approach!
Apply Through Our Website: Don't forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can't wait to see what you bring to the table!
How to prepare for a job interview at Eeze Entertainment Malta Limited
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals. Be ready to discuss your experience with SQL, Python, and any frameworks like Spark or Flink. They’ll likely ask you about your past projects, so have a couple of examples ready that showcase your skills in building data pipelines and models.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Highlight your attention to detail and troubleshooting abilities, especially when it comes to complex data issues. This will demonstrate your capability to handle the demands of the role.
✨Communicate Clearly with Stakeholders
Since you'll be collaborating with both technical and non-technical teams, practice explaining your technical work in simple terms. Think of examples where you successfully translated business requirements into data solutions. This will show that you can bridge the gap between data and business needs.
✨Familiarise Yourself with the Company’s Tech Stack
Do some research on the technologies the company uses, especially around data lakehouse or warehouse technologies like Delta Lake or Apache Hudi. Being knowledgeable about their tools will not only impress them but also help you understand how you can contribute effectively from day one.
