Data Engineers - Planning Inspectorate - HEO

Manchester Digital; Bristol; Hybrid; GBP 36,000 - 40,000; Full time

Job summary

A public sector organization is seeking a data engineer to lead in designing, implementing, and maintaining data systems. The role involves collaboration with various stakeholders and a strong understanding of SQL, Python, and Azure Data Factory. Based in Bristol, the organization offers a flexible hybrid working arrangement. The salary range is £36,396 - £39,424 with a standard working week of 37 hours.

Qualifications

• Ability to write optimized and maintainable SQL and Python for data warehousing.
• Practical experience of data engineering concepts, including modelling and quality assurance.
• Understanding of data governance principles and data security requirements.

Responsibilities

• Designing, implementing, and maintaining data systems to support the programme's success.
• Communicating updates and gathering input from stakeholders.
• Leading knowledge sharing efforts and collaboration between internal teams.

Skills

SQL

Python

Data modeling

Data integration

DevOps practices

Azure Data Factory

Agile methodologies

Tools

Microsoft SQL Server Integration Services

Azure DevOps

Job description

Overview

The Planning Inspectorate has a long and proud history in ensuring a fair planning system for England. The work we do has a significant impact on people’s lives, the communities where they live and the economy.

You will work with a smart and talented group of user researchers, product managers, DevOps engineers, testers, business analysts and delivery managers to deliver better public services for communities where they live; to deliver new and updated processes and systems for the Planning Inspectorate.

As the team is a multi-disciplinary team, you will be leading on the data conversations and aiding the team with planning, decision making and problem solving. There will be time spent also focusing on data design, implementation, stakeholder engagement and supporting with any training needed to technical and non-technical stakeholders.

You will be joining a wider team of highly skilled data architects and engineers, providing mentoring and guidance as well as setting the standard for technical excellence.

We want our colleagues to be able to work more flexibly and more collaboratively, exploring new and innovative ways to improve the way we provide services.

For further information on the Planning Inspectorate, please visit our careers page at Civil Service Careers.

Role and responsibilities

In this role, you\'ll play a key part in shaping the strategic direction of our reform programme, contributing to high level planning and decision making. You\'ll be responsible for designing, implementing, and maintaining the data systems that support the programme’s success. A big part of your day will involve working closely with stakeholders across the organisation including non-technical staff, senior leaders, and external partners, communicating updates, simplifying complex technical information, and gathering input to inform your approach. You\'ll also tackle challenges head on, using a mix of technical expertise and organisational insight to develop smart, effective solutions. Finally, you\'ll lead knowledge sharing efforts, ensuring smooth collaboration and training between our internal teams and external partners as we prepare for the work ahead.

Pay and working arrangements

This role is being advertised at HEO Grade.

Salary range for the Grade role is £36,396 - £39,424.

Working hours: Standard working week is 37 hours, flexible working hours policy available.

This role is contractually based at Temple Quay House, Bristol, which is currently out of use due to refurbishment work. In the interim, we have the use of alternative office space close to Bristol Temple Meads railway station. We recognise and value the mutual benefits of hybrid working and have a flexible approach to in-person attendance, which can vary depending on business needs and individual units. Details can be discussed with candidates if invited to interview.

Person specification

We will assess your application against the Essential Criteria and Success Profile elements listed:

• Ability to write optimized and maintainable SQL and Python for data warehousing, integration and transformation.
• Practical experience of data engineering concepts, including modelling, orchestration and quality assurance.
• Demonstrable experience in working with relational database systems and experience of using Azure Data Factory.
• Ability to diagnose and resolve data engineering issues, optimize data pipelines, and ensure high performance of data solutions.
• Understanding of data governance principles, data security, and privacy requirements. Knowledge of compliance standards like GDPR and Data Protection Act.
• DevOps and CI/CD: Experience with DevOps practices, including version control systems (e.g., Git), infrastructure-as-code concepts, and continuous integration and continuous deployment (CI/CD) processes. Knowledge of tools like Azure DevOps, or similar platforms for managing and automating data engineering workflows.
• Agile Methodologies: Understanding of Agile development methodologies, such as Scrum or Kanban. Ability to work collaboratively in an Agile team environment, participate in sprint planning, and deliver data engineering solutions iteratively.
• Understand the concept and uses of metadata.

Behaviours

We\'ll assess you against these behaviours during the selection process:

• Changing and Improving
• Communicating and Influencing
• Making Effective Decisions
• Working Together

Technical skills

We\'ll assess you against these technical skills during the selection process:

• Proficiency in working with relational database systems and experience of using Microsoft SQL Server Integration Services and/or Azure Data Factory.
• Ability to write optimised and maintainable SQL code for data warehousing, integration and transformation. Working knowledge of Python programming.
• Ability to diagnose and resolve data engineering issues, optimise data pipelines, and ensure high performance of data solutions.