Senior Data Engineer

Mountain Healthcare Ltd; Manchester; On-site; GBP 50,000 - 75,000; Full time

Job summary

A healthcare support team is seeking a Senior Data Engineer to enhance data flow management and support advanced analytics across the organization. The candidate will design and maintain data pipelines, collaborate across teams, and ensure data integrity aligns with best practices. With at least three years of industry experience and proficiency in SQL, Python, and cloud platforms, this role offers a competitive salary and a chance to impact service quality within the UK's healthcare landscape.

Qualifications

• At least 3 years industry experience.
• Experience in designing, building and maintaining data pipelines.
• Familiarity with creating ETL processes.

Responsibilities

• Designing and maintaining data pipelines.
• Building data warehouses and performing data cleansing.
• Ensuring data quality and compliance.

Skills

SQL

Python

R

Git

Data manipulation

Data analysis

Data modelling

Cloud platforms

Microsoft Excel

Problem-solving

Job description

Job summary

We are looking for an experienced Senior Data Engineer with strong technical expertise and innovative mindset to drive our team forward.
Main duties of the job

Data Engineer will be involved in the entire data pipeline from data acquisition to data extraction, ensuring that the data is accurate, reliable, and accessible, and fit-for-purpose for business intelligence, analytics, and data science functions. Data Engineer will be collaborating with cross-functional teams to support the delivery of impactful analytics work for our clients.
About us

We are the official research support team for the NHS Benchmarking Network, working with over 300 healthcare organisations across the UK to identify opportunities for service development and quality improvement.We also serve as the primary source of benchmarking data for the NHS England Workforce, Training and Education team, providing in-depth analysis across national mental health services. Our unique and comprehensive datasets support strategic decision-making and resource allocation across the UK healthcare system.In addition, we are proud to facilitate two major national audits: the National Audit for Care at the End of Life (NACEL) and the Cardiovascular Disease Prevention Audit (CVDPREVENT).

Job description

Job responsibilities

The primary purpose of the role is to be responsible for designing, building, optimising and maintaining the infrastructure that allows data to flow from various sources to storage systems, supports data storage, processing, and analysis, enables high-quality, secure, and scalable data delivery across the organisation. About the Role

1. Designing, building and maintaining data pipelines.
2. Building and maintaining data warehouses.
3. Data cleansing and transformation.
4. Developing and maintaining ETL processes (ELT = extract, transform, load) to extract, transform, and load data from various sources into data warehouses.
5. Validating charts and reports created by systems built in-house. Creating validation tools.
6. Developing and maintaining data models, data tools.
7. Monitoring and optimising the performance of data pipelines, data storage and processes, identifying and resolving bottlenecks to ensure efficient data processing and retrieval.
8. Ability to integrate data from multiple sources, including databases, APIs, websites, and flat files for efficient data processing.
9. Selecting and integrating appropriate tools and technologies
10. Troubleshooting and resolving data-related issues.
11. Architect scalable data solutions to support advanced analytics, machine learning, and real-time processing needs.
12. Design and implement data governance frameworks, including metadata management, lineage tracking, and cataloging.
13. Ensuring data quality and reliability; ensuring data security and compliance, including GDPR.
14. Document data engineering standards, design decisions, and infrastructure setup for operational transparency.
15. Collaborating with other teams to ensure data availability.
16. Collaborate with data scientists and analysts to ensure data availability for experimentation, model training, and deployment.
17. Defining and delivering clear data engineering work packages and deliverables.
18. Supporting the implementation of new infrastructure to improve the quality and efficiency of projects delivery.
19. Identify opportunities for innovation, improved productivity, efficiency, and quality.
20. Evaluate and prototype new tools or technologies, recommending enhancements to the existing data stack.

Job description
Job responsibilities

The primary purpose of the role is to be responsible for designing, building, optimising and maintaining the infrastructure that allows data to flow from various sources to storage systems, supports data storage, processing, and analysis, enables high-quality, secure, and scalable data delivery across the organisation. About the Role

1. Designing, building and maintaining data pipelines.
2. Building and maintaining data warehouses.
3. Data cleansing and transformation.
4. Developing and maintaining ETL processes (ELT = extract, transform, load) to extract, transform, and load data from various sources into data warehouses.
5. Validating charts and reports created by systems built in-house. Creating validation tools.
6. Developing and maintaining data models, data tools.
7. Monitoring and optimising the performance of data pipelines, data storage and processes, identifying and resolving bottlenecks to ensure efficient data processing and retrieval.
8. Ability to integrate data from multiple sources, including databases, APIs, websites, and flat files for efficient data processing.
9. Selecting and integrating appropriate tools and technologies
10. Troubleshooting and resolving data-related issues.
11. Architect scalable data solutions to support advanced analytics, machine learning, and real-time processing needs.
12. Design and implement data governance frameworks, including metadata management, lineage tracking, and cataloging.
13. Ensuring data quality and reliability; ensuring data security and compliance, including GDPR.
14. Document data engineering standards, design decisions, and infrastructure setup for operational transparency.
15. Collaborating with other teams to ensure data availability.
16. Collaborate with data scientists and analysts to ensure data availability for experimentation, model training, and deployment.
17. Defining and delivering clear data engineering work packages and deliverables.
18. Supporting the implementation of new infrastructure to improve the quality and efficiency of projects delivery.
19. Identify opportunities for innovation, improved productivity, efficiency, and quality.
20. Evaluate and prototype new tools or technologies, recommending enhancements to the existing data stack.

Person Specification

Qualifications

Essential

• Knowledge and proficiency in working with database systems (SQL/PostgreSQL) and writing performant SQL queries.
• Proficiency in optimising database queries, pipelines, and storage for speed, scalability, and cost-efficiency.
• Skilled in using Git.

Experience

Essential

• At least 3 years industry experience.
• Experience in R programming language.
• Experience in Python programming language.
• Experience in designing, building and maintaining data pipelines.
• Experience with data warehousing and data lakes.
• Experience in developing and maintaining ETL processes.
• Experience in developing data integration tools.
• Experience in data manipulation, data analysis, data modelling.
• Experience with cloud platforms (AWS, Azure, etc.)
• Experience in designing scalable, secure, and cost-efficient data architectures aligned with business needs.
• Strong track record of problem-solving ability and troubleshooting skills.
• Excellent IT skills including fluency with all Microsoft packages, particularly Excel, Word, PowerPoint, PowerBi.
• Evidence of excellent communication and interpersonal skills. Clearly communicate technical concepts to both technical and non-technical audiences.
• Adaptability and willingness to learn new technologies.

Person Specification
Qualifications

Essential

• Knowledge and proficiency in working with database systems (SQL/PostgreSQL) and writing performant SQL queries.
• Proficiency in optimising database queries, pipelines, and storage for speed, scalability, and cost-efficiency.
• Skilled in using Git.

Experience

Essential

• At least 3 years industry experience.
• Experience in R programming language.
• Experience in Python programming language.
• Experience in designing, building and maintaining data pipelines.
• Experience with data warehousing and data lakes.
• Experience in developing and maintaining ETL processes.
• Experience in developing data integration tools.
• Experience in data manipulation, data analysis, data modelling.
• Experience with cloud platforms (AWS, Azure, etc.)
• Experience in designing scalable, secure, and cost-efficient data architectures aligned with business needs.
• Strong track record of problem-solving ability and troubleshooting skills.
• Excellent IT skills including fluency with all Microsoft packages, particularly Excel, Word, PowerPoint, PowerBi.
• Evidence of excellent communication and interpersonal skills. Clearly communicate technical concepts to both technical and non-technical audiences.
• Adaptability and willingness to learn new technologies.

Disclosure and Barring Service Check

This post is subject to the Rehabilitation of Offenders Act (Exceptions Order) 1975 and as such it will be necessary for a submission for Disclosure to be made to the Disclosure and Barring Service (formerly known as CRB) to check for any previous criminal convictions.

Employer details

Employer name

Mountain Healthcare Ltd
Address

Manchester

City Of Manchester

M4 7DB

Employer's website