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- Tasks: Lead the design and development of data pipelines for analytics and AI.
- Company: Join a forward-thinking tech company focused on data innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team culture with mentorship opportunities and career advancement.
- Why this job: Make an impact by building cutting-edge data solutions in a collaborative environment.
- Qualifications: Experience with Python, SQL, and cloud data services is essential.
The predicted salary is between 55000 - 65000 £ per year.
Responsibilities
- Lead the design and development of robust data pipelines and data platforms to support analytics and AI workloads.
- Build and maintain batch and streaming data solutions, including ingestion, transformation, and orchestration.
- Design appropriate data models using relational, dimensional, or other modelling techniques, selecting approaches based on the requirements of analytics, reporting, and data science use.
- Collaborate across multiple teams and client stakeholders to design and deliver end-to-end data and AI solutions within the wider client technology landscape.
- Work across cloud-based data platforms and services (e.g. AWS, Azure, or GCP).
- Design and deliver data solutions that are functionally correct and fit for purpose, while meeting non-functional requirements such as security, performance, resilience, and maintainability.
- Support and guide junior engineers through technical leadership and mentoring.
- Contribute to platform and engineering standards, best practices, and continuous improvement across engagements.
Required Qualifications
- Bachelor's Degree in a related field.
- Strong experience with Python, SQL, and data engineering frameworks or tools.
- Proven experience designing and delivering data pipelines and data platforms in a professional environment.
- Hands-on experience with cloud data services (e.g. Azure Data Factory, Databricks, Synapse, AWS Glue, Redshift, BigQuery, or equivalents).
- Experience working with relational and/or NoSQL databases.
- Solid understanding of data modelling, integration patterns, and data quality principles.
- Strong problem-solving and communication skills, with experience working in multidisciplinary delivery teams.
Preferred Qualifications
- Familiarity with data pipeline orchestration tools (e.g., Apache Airflow, Luigi).
- Knowledge of data quality and metadata management practices.
- Understanding of data virtualisation and data federation techniques.
- Experience with big data technologies (e.g., Hadoop, Spark).
- Experience supporting analytics, data science, or machine learning use cases.
- Exposure to streaming or event-driven architectures (e.g. Kafka or equivalent).
- Experience with CI/CD, infrastructure as code, or platform automation.
- Background delivering solutions in regulated or security-constrained environments such as public sector or financial services.
This role is subject to pre-employment screening in line with the UK Government's Baseline Personnel Security Standard (BPSS). An additional range of Personal Security Controls referred to as National Security Vetting (NVS) may apply, which could include meeting the eligibility requirements for The Security Check (SC) or Developed Vetting (DV).
Data Engineer - Data & Analytics Platforms in Leicester employer: IBM
Contact Detail:
IBM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Data & Analytics Platforms in Leicester
✨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 and projects. This is your chance to demonstrate your expertise in Python, SQL, and cloud services. A strong portfolio can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss your past experiences. Confidence and clarity can make a huge difference!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Data Engineer - Data & Analytics Platforms in Leicester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience with Python, SQL, and any data engineering frameworks you've used. We want to see how your skills align with our needs!
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 team. Don't forget to mention any relevant projects or experiences that showcase your skills.
Showcase Your Projects: If you've worked on any cool data pipelines or platforms, make sure to include them in your application. We love seeing real-world examples of your work, especially if they relate to cloud services like AWS or Azure!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at IBM
✨Know Your Data Tools
Make sure you brush up on your knowledge of Python, SQL, and any data engineering frameworks you've used. Be ready to discuss specific projects where you've built data pipelines or platforms, especially using cloud services like AWS or Azure.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex data challenges in the past. Think about situations where you had to design data models or improve data quality, and be ready to explain your thought process.
✨Collaboration is Key
Since this role involves working with multiple teams, be prepared to talk about your experience collaborating with stakeholders. Highlight any instances where you successfully delivered end-to-end solutions and how you communicated with different teams.
✨Stay Current with Trends
Familiarise yourself with the latest trends in data engineering, such as big data technologies or event-driven architectures. Showing that you're up-to-date will demonstrate your passion for the field and your commitment to continuous improvement.