Research Projects Data Analyst - The National Archives - HEO (IT)

About the Role: As data analyst for these projects, you will design and develop scripts and tools to automate the processing and transformation of textual archival metadata. The most common data formats you will encounter are .csv, .xlsx .xml and .json. You will be based in our growing and vibrant Research, Grants and Academic Engagement Department, but will work with colleagues from across the organisation providing technical consultancy and solutions. Why Join Us? Within the beautiful surroundings of Kew, a 10-minute walk from the Underground and Overground stations, The National Archives boasts a collegial working environment and an excellent Civil Service benefits package. This includes flexible working, an on-site gym, and an opportunity to join the Civil Service Alpha Pension Scheme. Putting you at the forefront of our organisation, we are committed to supporting professional development and training for all of our colleagues. Job descriptionFull job description attached (see below). Person specificationThis is a full time post. However, requests for part-time working, flexible working and job share will be considered, taking into account at all times the operational needs of the Department. A combination of onsite and home working is available and applicants should be able to regularly travel to our Kew site for a minimum of 60% of their work time. Please note that candidates shortlisted for interview will take a technical test. How to apply: If you are an internal applicant: please do not use the link on this page. Please apply via your employee Workday account. If you are an external applicant: to submit your application please click the 'Apply at advertiser's site' button on this page. You will be asked to provide details of your work experience and write a personal statement, not exceeding 1200 words. In your statement please explain, using examples, how you meet the essential criteria below. You may draw on knowledge, skills, abilities, experience gained from paid work, domestic responsibilities, education, leisure interests and voluntary activities. Please note selection for interview will largely be based on the information you provide in this section. Artificial Intelligence can be a useful tool to support your application, however, all examples and statements provided must be truthful, factually accurate and taken directly from your own experience. Where plagiarism has been identified (presenting the ideas and experiences of others, or generated by artificial intelligence, as your own) applications may be withdrawn and internal candidates may be subject to disciplinary action. Please see our for more information on appropriate and inappropriate use. Candidate profile: Essential: Data technologies: excellent skills in pattern analysis with a broad knowledge and experience of relevant technologies for encoding, cleansing, manipulating and analysing complex structured and unstructured data. For example, data encoded in EAD or other XML, CSV and JSON. ETL processes: knowledge of how to extract data from various sources, including databases, APIs, and flat files and programmatic techniques in XPath, XSLT and Python or other modern programming languages. Demonstrable ability to clean, format, and transform data to meet the requirements of the target system. Skills in loading transformed data into target destinations or data models and vocabularies. Problem-solving: ability to identify and resolve issues that arise during the ETL and data migration processes. Experience in debugging and optimising ETL workflows for better performance, demonstrating a proactive and solutions focused approach to problems. Data governance: understanding of data governance practices, including data quality; reference and master data; data interoperability. Communication and relationships: strong communication and relationship building skills, able to communicate effectively with technical and non-technical stakeholders, support and host discussions within a multidisciplinary team, with potentially difficult dynamics, be an advocate for the team externally, and manage differing perspectives. Approach to work: exceptional accuracy and attention to detail. Strong organisational skills, motivated to work both independently and as a project team member. Demonstrable ability to prioritise tasks and deliver high quality work to agreed deadlines. Desirable: A strong focus on meeting user needs. Experience or awareness of Agile methodologies. Ability to manage projects (such as data transformation projects), including planning, execution, and monitoring progress. Good understanding of the value of records and archives.