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For Companies At a Glance
- Tasks: Develop and optimise data pipelines for high-volume healthcare data.
- Company: Join a leading organisation focused on transforming healthcare through data analytics.
- Benefits: Enjoy flexible working options, competitive salary, and opportunities for professional growth.
- Why this job: Make a real impact in healthcare by enhancing data systems and collaborating with diverse teams.
- Qualifications: Experience in healthcare data solutions and proficiency in SQL, Python, or Java required.
- Other info: Ideal for tech-savvy individuals passionate about data and healthcare innovation.
The predicted salary is between 48000 - 72000 £ per year.
Key aspects of the role include:
- Data Pipeline Development: Architect, develop, and optimise data extraction, transformation, and loading (ETL) processes for high-volume healthcare data.
- Integration of NHS Systems Data: Work directly with NHS data sources and ensure seamless integration of systems like UDAL, NCDR, SUS+, HES, and ODS into our analytics platform.
- System Performance: Monitor and enhance the performance of our data systems to ensure reliability and responsiveness.
- Collaboration: Partner with data scientists, analysts, and stakeholders to ensure that data solutions align with business needs and analytic strategies.
- Scalability & Security: Implement and enforce best practices for data security, quality, and scalability across our data infrastructure.
Essential Skills:
- Healthcare Data Expertise: Proven experience in designing and managing data solutions within healthcare environments. Demonstrated ability to work with NHS systems—such as UDAL, NCDR, SUS+, HES, and ODS—and to address the unique challenges these datasets present.
- Data Engineering Proficiency: Advanced proficiency in building and maintaining robust data pipelines using ETL tools and frameworks. Familiarity with data warehousing concepts and experience in developing scalable, high-performance data architectures.
- Technical Expertise: Strong command of SQL and scripting languages, along with experience in programming languages such as Python or Java. Experience with the Microsoft Azure ecosystem is essential, including proficiency with Azure Data Factory and Databricks, as these tools are integral to managing data within the UDAL platform.
- Data Quality and Governance: Experience in implementing data quality controls, data cleansing routines, and establishing governance frameworks to ensure data integrity and compliance with data security standards.
- Collaboration and Communication: Excellent communication skills with the ability to translate complex technical concepts to non-technical stakeholders. Proven experience working in cross-functional teams to deliver data-driven insights that support healthcare decision-making.
Desirable Skills:
- Advanced Analytics Integration: Experience integrating data engineering workflows with analytics platforms, including familiarity with business intelligence tools (e.g., Power BI, Tableau) and predictive analytics.
- Regulatory and Compliance Knowledge: Awareness of industry standards and regulations, particularly those applicable to healthcare data, with an emphasis on data privacy and security (e.g., GDPR, NHS Digital guidelines).
- Educational Background: Degree or equivalent in Computer Science, Data Engineering, or a related technical field; professional qualifications or certifications in data engineering or cloud technologies are a plus.
Senior Data Engineer employer: TTC Group
Contact Detail:
TTC Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Familiarise yourself with the specific NHS systems mentioned in the job description, such as UDAL and NCDR. Understanding how these systems operate and their data structures will give you a significant edge during interviews.
✨Tip Number 2
Showcase your experience with Azure Data Factory and Databricks by preparing examples of past projects where you've used these tools. Being able to discuss real-world applications will demonstrate your technical expertise effectively.
✨Tip Number 3
Brush up on your SQL and scripting skills, as these are crucial for the role. Consider working on sample data engineering projects or challenges that require you to build and optimise data pipelines.
✨Tip Number 4
Prepare to discuss how you've collaborated with cross-functional teams in the past. Highlighting your communication skills and ability to translate technical concepts for non-technical stakeholders will be key in demonstrating your fit for the role.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with healthcare data and NHS systems. Emphasise your proficiency in ETL processes, SQL, and any relevant programming languages like Python or Java.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data engineering in the healthcare sector. Mention specific projects or experiences that demonstrate your ability to integrate NHS systems and enhance data performance.
Showcase Technical Skills: Clearly outline your technical expertise, especially with Microsoft Azure tools like Azure Data Factory and Databricks. Provide examples of how you've implemented data quality controls and governance frameworks in previous roles.
Highlight Collaboration Experience: Discuss your experience working in cross-functional teams. Provide examples of how you've communicated complex technical concepts to non-technical stakeholders and contributed to data-driven decision-making in healthcare.
How to prepare for a job interview at TTC Group
✨Showcase Your Healthcare Data Expertise
Make sure to highlight your experience with NHS systems and the unique challenges they present. Be prepared to discuss specific projects where you've successfully managed healthcare data solutions.
✨Demonstrate Technical Proficiency
Be ready to talk about your skills in SQL, Python, or Java, and your experience with Azure Data Factory and Databricks. Consider preparing examples of how you've built and optimised data pipelines in previous roles.
✨Emphasise Collaboration Skills
Since this role involves working with cross-functional teams, share examples of how you've effectively communicated complex technical concepts to non-technical stakeholders. Highlight any successful partnerships with data scientists or analysts.
✨Discuss Data Quality and Governance
Prepare to explain your approach to implementing data quality controls and governance frameworks. Discuss any relevant experiences that demonstrate your commitment to data integrity and compliance with security standards.
