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For Companies At a Glance
- Tasks: Build and scale data infrastructure for AI-driven projects in a global marketplace.
- Company: Join a forward-thinking company at the forefront of engineering and analytics.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make an impact by enabling real-time analytics and supporting innovative AI solutions.
- Qualifications: 5+ years in Data Engineering with strong skills in Python, SQL, and cloud environments.
- Other info: Dynamic team environment with a focus on cutting-edge technology and career advancement.
The predicted salary is between 36000 - 60000 £ 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.
Key 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 in Essex 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 in Essex
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues 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 warehousing – make it shine!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your experience with ETL/ELT processes and cloud environments. Practise common interview questions and maybe even do some mock interviews with friends.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come directly from passionate candidates. Tailor your application to highlight your experience with ML/NLP workflows and data governance – it’ll make you stand out!
We think you need these skills to ace Data Engineer – AI in Essex
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-ready architecture. Keep it concise but engaging – we love a good story!
Showcase Your Technical Skills: When listing your technical skills, be specific! Mention your experience with ETL/ELT pipelines, cloud environments like AWS or GCP, and any exposure to ML/NLP workflows. We’re looking for those who can hit the ground running!
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’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at Datashrubs Technologies Ltd
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, SQL, and data modelling. Brush up on your experience with ETL/ELT pipelines and be ready to discuss specific projects where you’ve implemented these skills.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled challenges in building scalable data infrastructures. Think about times when you optimised performance or ensured data quality and governance, as these are key responsibilities for the role.
✨Familiarise Yourself with ML/NLP Workflows
Since the role involves enabling ML/NLP workflows, it’s crucial to understand how to prepare datasets for machine learning. Be ready to discuss any relevant experience you have and how you can contribute to this aspect of the job.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company’s data architecture, their use of BI tools, or how they approach data security and governance. This shows your genuine interest and helps you assess if the company is the right fit for you.