Principal Data Engineer

The opportunity

Our Quantexa Delivery team is all about bringing context to data. Principal Data Engineers are drivers within our fast-paced delivery teams, implementing Quantexa’s innovative technology for an ever-expanding list of domains including banking, insurance, government, healthcare. We are problem solvers, delivering sophisticated end-to-end big data solutions to our internal and external client stakeholders. As a central part of our team, you will experience opportunities beyond that of an engineer.

You will be the key technical decision maker for our delivery projects, balancing competing demands with technical complexity. You enjoy leading by example, guiding and mentoring data engineers to solve complex technical problems, sharing success with the team and taking pride in achieving milestones together. You share success with the team and take pride in the sum of its achievements. You will balance your time engaging with our business teams and clients to break down requirements into technical tasks, working hands-on as a programmer, and supporting the work of other engineers within a collaborative environment.

The work you do here will be impactful. The challenges we tackle are big, but they're also incredibly rewarding. Your leadership in managing, transforming, and cleansing high volume data help our clients solve business problems across a wide range of areas including fraud, financial crime, data management, risk and customer intelligence.

What you’ll be doing

• You will lead, support, and mentor a team of junior data engineers within an agile framework.
• You set medium term strategy for the technical delivery of delivery projects, seeking to anticipate challenges, risks and issues
• You operate with a high level of autonomy, seeking guidance and support from others as required
• Write defensive, fault tolerant and efficient code for production level data processing systems.
• You’ll configure and deploy Quantexa’s software using tools such as Spark, Hadoop, Scala, Elasticsearch, with our platform being hosted on both private and public virtual clouds, such as Google cloud, Microsoft Azure and Amazon.
• You will be a trusted source of knowledge to your clients. You will articulate technical concepts to a non-technical audience helping them to make big decisions.
• Collaborate with both our solution architects and our R&D engineers to champion solutions and standards for complex big data challenges. You proactively promote knowledge sharing and ensure best practice is followed.

What you’ll bring.

• You are an accomplished technical lead with a track record of delivering complex or mission critical projects, with at least eight years of industry experience in a data engineering role or engineering equivalent, and at least five years of experience acting in a lead role within a data or software engineering team across a range of projects.
• Proficiency in Scala, Java, Python, or a programming language associated with data engineering. Our primary language is Scala, but don’t worry if that’s not currently your strongest language, we believe that strong engineering principles are universal and transferrable.
• You’ll have expertise building and deploying production level data processing batch systems maintained by application support teams. Importantly you’ll share an appreciation of what makes a high quality, operationally stable system and how to streamline all areas of development, release, and operations to achieve this.
• Experience with a variety of modern development tooling (e.g. Git, Gradle, Nexus) and technologies supporting automation and DevOps (e.g. Jenkins, Docker and a little bit of good old Bash scripting). You’ll be familiar with developing within a version-controlled process that regularly makes use of these tools and technologies.
• A strong technical communication ability with demonstrable experience of working in rapidly changing client environments.
• Knowledge of testing libraries of common programming languages (such as ScalaTest or equivalent). Knows the difference between different test types (unit test, integration test) and can cite specific examples of what they have written themselves.

Nice to haves.

• Experience growing and up-skilling team members as a career mentor, technical line manager, or acting in an equivalent guidance role.
• A passion for expanding the business – and leading initiatives to do so.