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Data Engineer

2 months ago

Gloucester, United Kingdom Methods Full time

Methods Business and Digital Technology Limited

Methods is a £100M+ IT Services Consultancy who has partnered with a range of central government departments and agencies to transform the way the public sector operates in the UK. Established over 30 years ago and UK-based, we apply our skills in transformation, delivery, and collaboration from across the Methods Group, to create end-to-end business and technical solutions that are people-centred, safe, and designed for the future.

Our human touch sets us apart from other consultancies, system integrators and software houses - with people, technology, and data at the heart of who we are, we believe in creating value and sustainability through everything we do for our clients, staff, communities, and the planet.

We support our clients in the success of their projects while working collaboratively to share skill sets and solve problems. At Methods we have fun while working hard; we are not afraid of making mistakes and learning from them.

Predominantly focused on the public-sector, Methods is now building a significant private sector client portfolio.

Methods was acquired by the Alten Group in early 2022.

Requirements

The Data Engineer will:

Work with other members of the delivery team across a mix of large and small projects and be responsible for translating data into valuable insights that inform decisions for small to large transformation projects and programmes. Be responsible for identifying and using the most appropriate analytical techniques, developing fit-for-purpose, resilient, scalable and future-proof data services that meet user needs and design and write and iterate code from prototype to production-ready. Communicate effectively across organisational, technical and political boundaries to understand the context and how to make complex and technical information and language simple and accessible for non-technical audiences. Work with the others to support the growth and development of the team

Ideal Candidates will demonstrate:

Experience with Relational Databases and Data Warehousing experience such as SQL Server and/or Azure SQL SQL development experience including debugging and troubleshooting Have solid Relational Database design skills with an eye for performance optimisation Experience of programming in languages such as Python, Scala or Java Experience processing large volumes of structured/semi-structured data (CSV/JSON) Experience producing data models and understand where to use different types of data models Knowledge of data cleaning, wrangling, visualization and reporting, with an understanding of the best, most efficient use of associated tools and applications to complete these tasks Have cloud based experience, preferably with AWS and/or Azure Have experience with ETL / ELT Infrastructure, Azure Data Factory, Azure Synapse, SQL Server Integration Services (SSIS) Have experience with Analytical/Reporting tools SQL, Analysis Services, Power BI DevOps experience, such as using Git, CI/CD and Unit Testing Have attention to detail and ability to quality assure their own and other team members’ work Understanding of how to expose data from systems ( through APIs), link data from multiple systems and deliver streaming services. Know how to ensure that risks associated with deployment are adequately understood and documented. An ability to translate business requirements into technical specifications Experience of iterative/agile development methodologies such as SCRUM A good understanding of Data Governance principles and the safe handling and processing of Personal Identifiable Data

Desirable Skills & Experience:

Streaming and real-time data Knowledge of statistics principles necessary to interpret data and apply models. For example, knowledge of errors and confidence intervals to understand whether a relation seen in the data is real. Exposure to high performing, low latency or large volume data systems ( 1 billion+ records, terabyte size database) Understanding of distributed computing, columnar type databases, partitioning, map reduction Big Data Frameworks experience, such as Hadoop and Apache Spark Experience with NoSQL type environments, Data Lakes, Lake-Houses (Cassandra, MongoDB or Neptune)

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