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For Companies At a Glance
- Tasks: Source, clean, and transform data for analysis; build ML solutions for real-world applications.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Why this job: Make an impact by developing data solutions that drive decision-making and enhance business outcomes.
- Qualifications: Degree in computer science or data analysis; strong problem-solving and collaboration skills.
- Other info: Dynamic team environment with a focus on cutting-edge technologies and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
Responsibilities
- Data Acquisition & Preparation: Source, create, collect, clean, transform, and structure data for analysis and operational use, including synthetic data generation.
- Build and productionise ML/NLP solutions for legal and business use cases to enable better decision making.
- Feature Engineering & Integration: Develop new features, integrate data from internal/external sources, and create unified views to enhance performance and outcomes.
- Pipeline Development & Automation: Build, optimise, and automate scalable data pipelines using tools like Azure, Fabric, and Databricks; develop reusable components and templates.
- Governance, Quality & Security: Ensure data quality, governance, classification, retention, and robust security measures across the data lifecycle, supporting compliance and auditability. Contribute to standards, code reviews and communities of practice.
- Metadata & Semantic Services: Provide metadata management, define categories and relationships, and enable semantic capabilities for data discovery and interoperability.
- Monitoring & Issue Resolution: Monitor health and performance of data systems, identify and resolve quality issues, bottlenecks, anomalies, and validate data across environments.
- Analytics & Machine Learning Support: Apply analytics techniques, visualise data, prepare and serve data for machine learning, and collaborate with data scientists to operationalise models.
- Collaboration, Documentation & Standards: Work with stakeholders to deliver scalable data products, implement DataOps, telemetry, quality checks and CI/CD practices, maintain documentation, and promote adherence to architecture standards.
Qualifications
- Ideally degree educated in computer science, data analysis or similar.
- Strategic and operational decision-making skills.
- Ability and attitude towards investigating and sharing new technologies.
- Ability to work within a team and share knowledge.
- Ability to collaborate within and across teams of different technical knowledge to support delivery to end users.
- Problem-solving skills, including debugging skills, and the ability to recognise and solve repetitive problems and root cause analysis.
- Ability to describe business use cases, data sources, management concepts, and analytical approaches.
- Experience in data management disciplines, including data integration, modeling, optimisation, data quality and Master Data Management.
- Excellent business acumen and interpersonal skills; able to work across business lines at all levels to influence and effect change to achieve common goals.
- Proficiency in the design and implementation of modern data architectures (ideally Azure / Microsoft Fabric / Data Factory) and modern data warehouse technologies (Databricks, Snowflake).
- Experience with database technologies such as RDBMS (SQL Server, Oracle) or NoSQL (MongoDB).
- Knowledge in Apache technologies such as Spark, Kafka and Airflow to build scalable and efficient data pipelines.
- Ability to design, build, and deploy data solutions that explore, capture, transform, and utilise data to support AI, ML, and BI.
- Proficiency in data science languages / tools such as R, Python, SAS.
- Awareness of ITIL (Incident, Change, Problem management).
Data Engineer in Newcastle upon Tyne employer: Norton Rose Fulbright
Contact Detail:
Norton Rose Fulbright Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer in Newcastle upon Tyne
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with data engineers 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 projects, especially those involving Azure, Databricks, or any cool ML/NLP solutions you've built. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Be ready to discuss how you've tackled data quality issues or optimised pipelines in the past. Real-world examples will make you stand out!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace Data Engineer in Newcastle upon Tyne
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your experience with data pipelines, ML/NLP solutions, and any relevant technologies like Azure or Databricks.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering. Share specific examples of how you've tackled challenges in data management or pipeline development, and how you can contribute to our team.
Showcase Your Projects: If you've worked on any relevant projects, whether personal or professional, make sure to mention them. We love seeing practical applications of your skills, especially if they involve data integration or analytics.
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 shows us you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Norton Rose Fulbright
✨Know Your Data Tools
Familiarise yourself with the specific tools mentioned in the job description, like Azure, Databricks, and Fabric. Be ready to discuss your experience with these technologies and how you've used them to build and optimise data pipelines.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled data quality issues or bottlenecks in previous roles. Highlight your debugging skills and your approach to root cause analysis, as these are crucial for a Data Engineer.
✨Understand the Business Context
Be prepared to explain how your technical skills can translate into business value. Think about specific use cases where your data solutions have enabled better decision-making or improved outcomes.
✨Collaboration is Key
Since this role involves working with various stakeholders, be ready to discuss your experience in collaborative environments. Share examples of how you've worked across teams to deliver scalable data products and maintain documentation.
