Location: Telephone House, 69-77 Paul Street, London EC2A 4NW
Salary: £50,000 – £55,000, plus benefits and discretionary bonus
Role overview (click here to find out more about Profusion and staff benefits):
We are currently looking for an outstanding Data Engineer to join our growing analytics and data science team. If you are successful you will have the opportunity to work with blue-chip clients on cutting-edge data science and innovative data driven marketing solutions. Many of our clients are embarking on game-changing digital and data transformation projects that will fundamentally change how they operate. You will be in a pivotal position to help our clients and Profusion undertake these cutting-edge projects that have industry-wide impact.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimising data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects for both internal and external clients.
You must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimising or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
You will have good potential for personal and career development, learn from and share knowledge with a range of talented, highly skilled and internationally diverse team of colleagues. All of this while embarking on an exciting journey with a pioneering, fast-growing company situated at the heart of London’s Tech City.
This is a team-based role, where the project work is varied and shared amongst other engineers so you will not just be focused on one part of the process, so being able to see the big picture and work collaboratively is critical. The role will have a 70% focus on client projects and 30% internal projects.
- Working with a team of analysts, data scientists and data engineers amongst other stakeholders to identify and implement best solutions for the analytical needs of a project
- Contributing to architectural designs, engaging in technical discussions and presenting solutions to product challenges
- Work with our technical partners and suppliers to ensure their technology is implemented for our internal requirements and for our client projects
- Work with our internal operations team to ensure business intelligence is duly applied across all sections of the business
- Lead by example and ensure the development and learning of junior team members
- Heavily involved in the building and development of the architecture and engineering process of projects including building API’s as well as other scripts to set up and automate engineering pipelines and solutions
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Create data tools for analytics and data scientist team members that assist them in building and optimising our products and services into an innovative industry leader.
- Someone who can complement the commercial and sales teams, supporting client meetings, pitches and add value to client proposals, new business strategy and company case studies.
Personal Specification: Knowledge, Experience and Skills
We are looking for a candidate with 3+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field, or relevant industry experience.
Knowledge & Experience
- Architected end-to-end solutions for clients in a fast paced agile, environment
- Experience of working collaboratively across team, to ensure learning and development of platforms, databases, schemas and coding standards
- Experience with embedding analytics within a business intelligence toolset
- Experience of working with high velocity and high-volume data
- Strong background in handling relational, semi-structured and unstructured data.
- Worked extensively in building scalable and high-performant code fit for production
- Determined technology choices and infrastructure on a project by project, case by case basis to ensure costs are kept to a minimum and technology is kept to a cutting-edge standard.
- Educated new business and other members of the company on the area of expertise and new project potentials.
- Strong technical background gained through delivery of client projects
- Extensive experience of bringing together data sources (both open and proprietary)
- Strong SQL knowledge and experience, working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Strong experience with at least one business intelligence tool – we use Sisense but Tableau, PowerBI, Qlik experience is great too!
- NoSQL such as MongoDB
- Big data technology such as Hadoop.
- Deep AWS understanding (S3, Lambda, API Gateway, Redshift, micro-services and serverless architecture, IAM authentication and policy management)
- Strong analytic skills related to working with unstructured datasets
- Strong Python programmer
- Understanding of network infrastructure and strong aptitude for using Linux
- Devops skillset such as Docker, Vagrant, Jenkins
- Experience with efficiently pulling from API’s
Personal skills and competencies
- Strong problem-solving skills, willingness to take ownership and risks, and enthusiasm in the face of technical challenges
- Strong project management and organisational skills, with the ability to prioritise and meet deadlines in a calm and effective way
- Excellent interpersonal skills and the ability to work in a team environment
- Strong communication skills, with the ability to support client meetings
- Client focused, with the ability to interpret and understand client needs and deliver results
- The ability to understand the wider company operations, goals and objectives and where data engineering can add value
- A proactive approach and the ability to be self-managing and innovative.
How to apply
If you are passionate about a career in data engineering and you meet the requirements above, please email your CV with a cover letter (no more than 2 sides of A4) outlining why you would be ideal for the role to: email@example.com (Closing date for applications is 5th November 2019).
Please note that because of the high number of applications we typically receive, it is not possible to answer everyone in person, successful candidates will hear from us within 2 weeks of the closing date.