Data Engineer

Company Overview

Quotient Sciences is a drug development and manufacturing accelerator providing integrated programs and tailored services across the entire development pathway. Cutting through silos across a range of drug development capabilities, we help biotech and pharma customers save precious time and money in getting drugs to patients.

As a growing and successful business, we employ more than 1,300 talented individuals globally, located at state-of-the-art development, manufacturing and clinical facilities in the UK and USA.

Science, Agility and Culture are the core components that define Quotient Sciences, enabling us to do what we do in the way that we do it. People join Quotient Sciences because we are a respected member of the drug development community that’s focused on innovation and are driven by an unswerving belief that ideas need to become solutions, and molecules need to become cures, fast. Because humanity needs solutions, fast. 

The Role

The Data and Analytics team is an integral part of the business. We build and deliver the data infrastructure that powers our analytics activity, allowing us to drive value from our data via the provision of analysis, reporting and insights internally to teams across the full span of the business.

We’re looking for an exceptional Data Engineer to join the team and contribute towards the building of new data architecture and delivery of cutting-edge solutions using advanced tools and technologies in the Data and Analytics space.

The role requires a strong technical understanding of data platforms, data warehousing and visualisation tools. You’ll need to be adaptable, flexible and resourceful in delivering a challenging roadmap whilst our data landscape is transforming. This is a crucial appointment and an amazing opportunity for an ambitious Data Engineer looking to be part of a growing part of the business.

Key responsibilities:

• Design and develop scalable, reliable, and efficient cloud-based data-warehousing infrastructure as a single source of truth for Quotient’s data assets.
• Map, learn and understand a broad range of Quotient data resources and help progressively integrate them into the data warehouse over time using repeatable ETL pipelines.
• Develop and maintain data engineering tools for automation, monitoring and alerting of the data pipelines. Continuously monitor and fine-tune the performance of the platform to meet SLAs and optimise resource utilisation, enabling efficient data access for analytical needs.
• Implement robust data quality checks and monitoring systems to ensure accuracy, consistency, and reliability of data.
• Development of technical solutions that fit into the overarching architecture, technology and data strategy.
• Work alongside our BI Analysts and use a range of analytical techniques to solve complex problems and drive decision making (key topics include pricing, customer analytics, forecasting, operational effectiveness, drug discovery, etc.,)
• Work as part of an Agile team to deliver business-focused requirements on the data platform
• Implement and enforce best practices for the use of data technologies and coding practices.
• Develop and share knowledge on new technologies across our analytics community
• Contribute to the evolution of the platform by evaluating new technologies and building prototypes covering topics such as machine learning, streaming or API-driven services.
• Build data expertise and leverage data controls to ensure privacy, security, and compliance.

The Candidate

Essential technical skills:

• 2+ years’ experience in hands-on Data Engineering roles (ideally with direct experience in a low maturity company transforming its Data and Analytics estate)
• Strong experience with cloud-based data platforms, preferably AWS (including services such as Glue, Lambda, S3, Athena etc.)
• In-depth knowledge of data modelling, data warehousing, and ETL/ELT processes.
• Proven experience in data pipeline development, and expertise in ETL tools (such as DBT, Matillion etc.)
• Highly proficient in SQL/T-SQL. Knowledge and practical of application of Python.
• Experience in integrating datasets from disparate online and offline data sources and systems.
• Data performance management experience – performance optimisation and tuning of data pipelines and database queries.
• Experience of delivery of scale data engineering, integration and analytics projects

Non-technical skills:

• Strong architecture design skills; being able to discuss design and trade-offs of different approaches and technologies
• Naturally inquisitive, with an eye for detail and the willingness to learn new tools and techniques.
• A methodical, analytical, and logical thinker with the ability to see the bigger picture and get to the underlying business questions and challenges that need answering.
• Outstanding numerical, technical, and problem-solving skills.
• Ability to build and maintain strong relationships with both technical and non-technical colleagues, translating complex concepts into simple terms where required.
• A team player with a passion for working in a collaborative environment.
• Extremely organised, delivery focused, and deadline driven. The ability to prioritise workload and manage stakeholders effectively.
• Applied knowledge of Agile principles and frameworks like Kanban and Scrum. Roadmap delivery using tools like Jira.
• Good commercial awareness.
• The ability to thrive in a risk-taking, fast-paced environment. Enjoy a hands-on role.
• Ambitious and proactive.
• A confident and conscientious communicator.

Desirable skills:

• Strong understanding of application security concepts, including securing production applications and delivery pipelines
• Strong understanding of data governance concepts such as data ownership and data stewardship
• Experience in end-to-end data orchestration – knowledge of workflow scheduling tools such as Oozie or Airflow
• Experience and knowledge of the pharmaceutical industry and associated data
• Knowledge and experience using other programming and/or statistical languages (e.g., Python, R etc.).
• Release management experience using tools such as Github or Jupyter notebooks.
• Experience in the usage of data visualisation tools, such as Tableau

Company Benefits

In return, you will receive a competitive salary, a generous benefits package, excellent training and development, as well as an exciting career within a fast paced and dynamic business.

Our Commitment to Diversity, Equity and Inclusion

Quotient Sciences are advocates for positive change and conscious inclusion. We strive to create a diverse Quotient family and develop a workplace culture that provides a sense of acceptance for every person within our organisation. As a global employer, we recognise the value in having an organisation that is a true reflection and representation of our society today. All applicants are welcome.