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For Companies At a Glance
- Tasks: Design and build scalable data pipelines for a modern cloud-based data platform.
- Company: Fast-growing tech organisation focused on innovation and data-driven decisions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a dynamic team and shape the future of data analytics in a tech-driven environment.
- Qualifications: Strong experience in data engineering, advanced SQL skills, and cloud platform familiarity.
- Other info: Collaborative culture with excellent career advancement opportunities.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for a skilled Senior Data Engineer (Analytics) to play a key role in building and scaling a modern, cloud-based data platform for a fast-growing, technology-driven organisation. This role sits at the intersection of data engineering and analytics, with a strong emphasis on designing robust data pipelines, developing high-quality datasets, and enabling self-service analytics across the business. You will help shape a scalable data ecosystem that empowers teams to make data-driven decisions through accessible, reliable, and well-structured data. The environment prioritises simplicity, maintainability, and scalability, leveraging cloud-native tooling and configuration-driven approaches over complex custom builds. Working across AWS and Azure, you will contribute to a modern data platform incorporating cloud data lakes, warehouses, and BI tools, supporting both internal analytics and customer-facing data solutions.
Key Responsibilities
- Design, build, and maintain scalable data pipelines using modern ELT frameworks (e.g. Azure Data Factory, Airflow or similar)
- Develop and optimise analytics-ready datasets to support reporting, operational insights, and downstream applications
- Work with a variety of data sources including APIs, relational databases, and semi-structured data stores
- Improve and maintain existing Python-based data workflows and orchestration processes
- Ensure data pipelines are robust, efficient, and support incremental processing
- Monitor, troubleshoot, and optimise pipeline performance and query efficiency
- Support and enable self-service analytics by delivering well-structured, trusted datasets
- Collaborate with engineering, product, and business teams to define and deliver data requirements
- Contribute to data architecture decisions, tooling selection, and platform improvements
- Implement and maintain data governance, security, and access controls (e.g. RBAC)
- Integrate with third-party systems and external data providers via APIs
- Support the delivery of embedded or customer-facing analytics solutions
Skills & Experience
Core Requirements
- Strong experience in a Data Engineering or Analytics Engineering role
- Advanced SQL skills and solid understanding of data modelling principles
- Experience building and maintaining data pipelines in cloud environments
- Strong problem-solving skills with the ability to translate business needs into data solutions
- Experience working with large-scale and/or complex datasets
- Familiarity with performance tuning and optimisation across data pipelines and queries
- Strong communication skills and ability to work cross-functionally
Technical Experience (examples)
- Cloud Platforms: AWS and/or Azure
- Data Storage & Processing: Data warehouses, data lakes, and databases (e.g. Redshift, Snowflake, BigQuery, S3, Azure Data Lake)
- ELT / Orchestration Tools: Azure Data Factory, Apache Airflow, AWS Glue, Matillion or similar
- Programming: Python (or similar for data processing and orchestration)
- BI & Visualisation: Power BI, Tableau, or similar tools
- Data Types: Structured and semi-structured data (e.g. JSON, document stores)
- Experience with data security and access control frameworks (e.g. RBAC, identity providers)
- Experience integrating external APIs and third-party data services
- Exposure to regulated or data-sensitive environments
- Experience evaluating and selecting data tools and vendors
Senior Data Engineer in Manchester employer: TrueNorth
Contact Detail:
TrueNorth Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in Manchester
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in a Senior Data Engineer role. Building relationships can lead to insider info on job openings and even referrals.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your data pipelines, analytics projects, or any cool stuff you’ve built. This gives potential employers a tangible sense of what you can do.
✨Ace the Interview
Prepare for those interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process when solving problems, as this shows your analytical skills and how you approach challenges.
✨Apply Through Our Website
When you find a role that excites you, 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 genuinely interested in joining our team.
We think you need these skills to ace Senior Data Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your experience with cloud platforms like AWS and Azure, and don’t forget to showcase your advanced SQL skills!
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 your background aligns with our mission at StudySmarter. Keep it concise but impactful!
Showcase Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to mention them. We love seeing real-world applications of your skills, especially in building scalable data pipelines or optimising datasets.
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!
How to prepare for a job interview at TrueNorth
✨Know Your Data Tools
Make sure you’re well-versed in the specific tools mentioned in the job description, like Azure Data Factory and Apache Airflow. Brush up on your SQL skills and be ready to discuss how you've used these tools in past projects.
✨Showcase Problem-Solving Skills
Prepare examples of how you've tackled complex data challenges. Think about times when you translated business needs into effective data solutions, and be ready to explain your thought process during the interview.
✨Understand the Cloud Environment
Since this role involves AWS and Azure, make sure you can speak confidently about your experience with cloud platforms. Be prepared to discuss how you’ve built and maintained data pipelines in these environments.
✨Communicate Cross-Functionally
Highlight your ability to work with different teams. Prepare to share experiences where you collaborated with engineering, product, or business teams to define data requirements and deliver successful outcomes.