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Lead Software Engineer-Data Platforms

Richmond, Greater London

Competitive

Permanent

About Reed Exhibitions

Reed Exhibitions is a leading global events organiser, with more than 500 events in 30 countries. In 2018, Reed Exhibitions brought together more than 7m event participants from around the world generating billions of dollars in business. Today Reed Exhibitions’ events are held throughout the Americas, Europe, the Middle East, Asia Pacific and Africa and organised by 38 fully staffed offices. Reed Exhibitions serves 43 industry sectors with trade and consumer events. It is part of RELX, a global provider of information and analytics for professional and business customers across industries.

About RELX

RELX is a global provider of information-based analytics and decision tools for professional and business customers. The Group serves customers in more than 180 countries and has offices in about 40 countries. It employs over 30,000 people, of whom almost half are in North America.

The Role

RX Global Technology is leading business transformation in a dynamic and fast changing industry. This is an exciting and growing team, delivering high profile programs that facilitate millions of meaningful business connections, drive increased customer value and enable more productive working across our truly international business. We value an agile approach, a growth mindset and an entrepreneurial spirit. In return, we offer a competitive salary, great benefits, flexible working, and you’ll be supporting our 520 shows in 43 industry sectors and 30 countries, producing events like Comic Con and Gamer Network among many others. The OpportunityWe are developing new capabilities with data to deliver product insights, enable data science-led insights into our global events and deliver new innovative data products. Working as part of a highly motivated, collaborative, enthusiastic, distributed, cross-functional team. Your knowledge and expertise will support designing data architectures, and determining technologies and tools for storage and large-scale processing of data. You will collaborate closely with software engineers in building integrations with services owned by other teams. Partnering closely with the Product Owner, and offshore peers, to develop new business capabilities which follow standards and are easy to support. Also working with data scientists and stakeholders to ensure that our data platforms provide continuous value to our business in the form of monitoring, reporting, and predictive and prescriptive insights. Using a modern tech stack and agile & DevOps principles to deploy high quality changes to production with confidence safely and reliably.

Key Accountabilities

You are responsible for adding value and creating business impacts for Reed Exhibitions in the following areas:

Product Leadership: The focus is on delivering data-led products and services on time and above customer expectations, understanding lifetime value concepts, being close to the customer and creating impacts.

Excellence: The focus is on simplification, innovation, clean design, efficiency, streamlined operations, delivery, high quality, reliable, secure solutions and long-term sustainability.

Teamwork: The focus is on collaboration, communication, support, being an SME, continuous improvement, having a collective shared responsibility for solutions, and delivering outcomes.

Problem solving: The focus is on being a professional with a questioning mind-set, who utilises systems thinking and enjoys investigating, acting and feeling responsible for delivering results

Skills and Experience

As a Senior Data Engineer/Developer with experience implementing enterprise scale relational & NoSQL/big data solutions having led the discovery, architecture, design, planning, deployment and maintenance of data-led solution.

You should also have experience of running, enhancing and optimisation techniques for high volume usage such as sharding, clustering, distribute datasets, indexing strategies, IO, caching, reporting, BI, and security/access controls.

Experience of transferring high volume data between database and business systems and of automating such processes.

You should demonstrate building team and stakeholder confidence through deep knowledge, and being collaborative and customer focused.

You will have extensive experience of collaborating with business and data scientists to maximise their value through learning, optimisation and innovation.

Confident in your ability rapidly to learn the technologies, you will be a life-long learner and follower of continuous improvement principles, which you apply in your professional development as well as those of your systems.

At ease with troubleshooting in complex environments, with experience of profiling, high volume logging strategies and log analysis.

You actively participate in the data engineering community. Relevant Technology & Practices You will have experience in many of the following technologies and practices, or equivalent, and be ready to learn where gaps exist.

Agility: Scrum, Kanban, cross-functional teams

Design: Relational and non-relational (NoSQL, big data) data store design, Cloud data storage formats and techniques, transformation/querying techniques, ETL, map reduce, projections, data warehouse and data lake solutions.

Languages & Interfaces: In-depth experience of SQL, S3, Hadoop, Redshift, Glue, ElasticSearch, PowerBI. At least one programmatic language, e.g. C , Java, Python, R.

Scale: Expert in optimisation tools and practices: profilers, loggers, indexing strategies, clusters, sharding

Business information: Familiarity with BI/MI concepts, multi-dimensional data repositories, warehouses, lakes. Statistical functions, multi-dimensional array transposition and aggregation, value conversion, formatting, localisation, integrity preservation, data science concepts (data mining, machine learning)

Software Factory: Familiarity with current software development practices: CI/CD, automated testing, blue/green deployment, feature toggles.

Cloud: Demonstrable commercial exposure to at least one enterprise cloud environment, e.g. AWS, Azure, Google. Exposure to AWS products (S3, SQS, Athena, SNS, Lambdas) highly beneficial.

Posted 13 days ago

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