Description
Key skills and knowledge Experience (Very Important)
* Experience of working on Azure cloud technologies such as Azure Data Factory, Azure Databricks, Azure Data Lake, Azure VM, Azure App Services, Azure Functions, Azure Log Analytics, Azure Monitor, etc
* Experience of coding in Python, R, Spark, .Net, PowerShell or similar.
* Experience of working with APIs, SFTP, Gateway, JSON and Parquet file formats
* Experience of working with Power platform services like Power Apps, Power Automate and Power BI
* Proven experience of working with both structured and schema-less databases/storage such as Delta Lake, Cosmos DB, MongoDB, Azure SQL, Oracle, and SQL Server
* Experience of working with DevOps principles, ADO GIT Repo, IaC release process, automated CI/CD pipelines, etc
* Proven experience of working with large and complex structured and unstructured data.
* Experience of coding and automating data pipelines and building data validation processes.
* Experience developing and maintaining effective working relationships with technical and non-specialist colleagues.
* Evidence of adaptability; able to learn new technologies and methodologies quickly.
* Demonstrable experience in a role that includes problem solving, analytical and logical skills. Skills
* Efficiently collecting, manipulating and validating large and complex datasets.
* Designing and building data models and services.
* Comfortable giving definition to ambiguous problems, can do this independently with limited guidance.
* Solid understanding of software design principles and Agile best practice.
* Verbal/written communication & data presentation skills, including experience of effectively communicating with both business and technical teams.
* Strong analytical skills with the ability to collect, organise, analyse, and disseminate significant amounts of information with attention to detail and accuracy. Qualifications:
* Degree level qualification and/or appropriate professional qualifications/membership or equivalent experience (5+ years of delivering in an enterprise environment).
Key competencies
1. Analysis and Planning Thinks logically and analytically to get to the core of problems; manages and assimilates complex information resulting in effective decisions based on sound commercial knowledge and expertise. Works quickly and accurately through the planning and prioritising of own workload.
2. Focus on results Looks critically at systems, policies, processes and procedures. Understands business requirements and collaborates with colleagues to deliver positive outcomes.
3. Creative Thinker Challenging the conventional way of doing things, generates new ideas and commercial solutions in order to improve performance and delivery.
Key performance measures
1.High quality data assets delivered across the agency which contribute to improved data understanding, quality and use in decision making.
2. Time taken to generate actionable intelligence from raw data.
3.Mutually beneficial relationships established and maintained with colleagues across the business.
Values and key behaviours
1 Creative - suggest and implement improvements, strategies and systems - based on experience and knowledge of the business - to improve activities, processes and attitudes towards data.
2 Collaborative - work with a wide variety of colleagues from within and outside of the business; listening to viewpoints and appreciating the perspective of others whilst delivering own role.
3 Ambitious - strive to deliver efficient and effective data solutions for the business and the Agency.