At a Glance
- Tasks: Design and build modern data platforms while ensuring security and compliance.
- Company: Join Simple Machines, a global tech consultancy transforming data into actionable insights.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and a focus on engineering excellence.
- Why this job: Make a real impact by shaping innovative data solutions for diverse clients.
- Qualifications: Strong Python and SQL skills, with experience in Spark and cloud data services.
The predicted salary is between 59400 - 72600 £ per year.
Описание: Simple Machines is a global, independent technology consultancy that designs and builds modern data platforms, intelligent systems, and bespoke software across data engineering, software engineering, and AI.
It helps enterprises, scale-ups, and government turn complex data into products, platforms, and actionable decisions.
- Задачи
- Own the end-to-end architecture of modern, cloud-native data platforms
- Design scalable data ecosystems using data mesh, data products, and data contracts
- Make architectural decisions across ingestion, storage, processing, and access layers
- Ensure platforms are secure, compliant, and production-grade by design
- Design and deliver cloud-native data platforms using Databricks, Snowflake, AWS, and GCP
- Integrate with client systems to enable scalable, consumer-oriented data access
- Build and optimise batch and real-time pipelines
- Work with streaming and event-driven technologies such as Kafka, Flink, Kinesis, and Pub/Sub
- Orchestrate workflows using Airflow, Dataflow, and Glue
- Process and transform large datasets using Spark and Flink
- Design production-ready systems
- Work across relational, No SQL, and analytical data stores
- Optimise storage formats and access patterns
- Implement secure, compliant data solutions with security by design
- Embed governance while maintaining developer velocity
- Work directly with clients to understand problems and shape solutions
- Translate business needs into pragmatic engineering decisions
- Act as a trusted technical advisor
- Set engineering standards, patterns, and best practices across teams
- Review designs and code, providing technical direction and mentorship
- Improve data quality, testing, observability, and operational excellence
- Требования
- Strong Python and SQL skills
- Deep experience with Spark and modern data platforms such as Databricks and Snowflake
- Solid understanding of cloud data services in AWS or GCP
- Demonstrated ownership of large-scale data platform architectures
- Strong data modelling and architectural decision-making skills
- Ability to balance performance, cost, and complexity trade-offs
- Experience building and operating large-scale data pipelines in production
- Experience with multiple storage technologies and formats
- Infrastructure-as-code experience with Terraform or Pulumi
- Experience with CI/CD pipelines using tools such as Git Hub Actions or Argo CD
- Experience with data testing and quality frameworks such as dbt, Great Expectations, or Soda
- Experience in consulting or professional services environments
- Strong consulting instincts and ability to challenge assumptions and guide clients toward better outcomes
- Ability to mentor senior engineers and influence technical culture
- Условия
- No conditions specified
- #J-18808-Ljbffr
data engineer in data platforms employer: Enfint
As a leading innovator in AI products for major publishers, our company offers an inspiring work environment where creativity and technology intersect. We prioritise employee growth through continuous learning opportunities and foster a collaborative culture that values diverse perspectives. Located in a vibrant city, we provide competitive salaries, relocation support, and the chance to make a real impact in the media landscape.
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We think this is how you could land data engineer in data platforms
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We think you need these skills to ace data engineer in data platforms
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 Enfint
✨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!
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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 Enfint!
✨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.
