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- Tasks: Build and scale data infrastructure for our global engineering marketplace and analytics.
- Company: Join a leading company in AI and analytics with a focus on innovation.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make an impact by enabling real-time analytics and supporting decision-making with trusted data.
- Qualifications: 5+ years in Data Engineering with strong skills in Python, SQL, and data modelling.
- Other info: Dynamic work environment with a focus on cutting-edge technology and career advancement.
The predicted salary is between 48000 - 72000 £ per year.
We are looking for a Data Engineer to build and scale the data infrastructure, pipelines, and AI-ready architecture powering our global engineering marketplace, revenue intelligence, and product analytics. This role ensures accurate GMV/revenue data, real-time analytics, and ML/NLP-ready datasets for decision-making and investor reporting.
Responsibilities:
- Design and maintain scalable ETL/ELT pipelines using Python and SQL
- Build data warehouse models for revenue, users, and product analytics
- Enable ML/NLP workflows with clean, feature-ready datasets
- Deliver trusted data to BI dashboards and optimize performance
- Implement data quality, security, and governance controls
Required Experience:
- 5+ years in Data Engineering or Analytics Engineering
- Strong record of building production-grade pipelines and warehouses
Technical Skills:
- Python, SQL, data modeling
- Airflow/dbt, modern data warehouses (Snowflake/BigQuery/Redshift)
- AWS/GCP/Azure cloud environments
- Exposure to ML/NLP data preparation and BI tools (Power BI/Tableau/Looker)
Data Engineer – AI & Analytics Platform in Clacton-on-Sea employer: Datashrubs Technologies Ltd
Contact Detail:
Datashrubs Technologies Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer – AI & Analytics Platform in Clacton-on-Sea
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, models, and any cool projects you've worked on. This is your chance to demonstrate your expertise in Python, SQL, and data modelling.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with ETL/ELT processes and how you've tackled challenges in building scalable data infrastructures.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer – AI & Analytics Platform in Clacton-on-Sea
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in Data Engineering and showcases your skills in Python, SQL, and data modelling. We want to see how your background aligns with the role, so don’t be shy about mentioning relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our AI & Analytics Platform. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you've worked on any cool data pipelines or analytics projects, make sure to mention them! We’re interested in seeing real examples of your work, especially those that demonstrate your ability to build scalable solutions and handle ML/NLP workflows.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter!
How to prepare for a job interview at Datashrubs Technologies Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, and the specific data warehousing tools mentioned in the job description. Brush up on your knowledge of Airflow, dbt, and cloud environments like AWS or GCP. Being able to discuss your experience with these technologies will show that you're ready to hit the ground running.
✨Showcase Your Pipeline Experience
Prepare to talk about your past projects where you built production-grade ETL/ELT pipelines. Be ready to share specific examples of challenges you faced and how you overcame them. This will demonstrate your problem-solving skills and your ability to deliver trusted data.
✨Understand ML/NLP Workflows
Since the role involves enabling ML/NLP workflows, it’s crucial to have a solid understanding of how to prepare datasets for machine learning. Brush up on your knowledge of feature engineering and be prepared to discuss how you’ve worked with clean, feature-ready datasets in the past.
✨Data Quality and Governance Matters
Be ready to discuss how you ensure data quality, security, and governance in your work. Companies want to know that you can implement controls effectively. Share any frameworks or best practices you follow to maintain high standards in data management.
