As a Data Engineer, you will be responsible for building and maintaining MarSci’s data pipelines, ensuring seamless integration of various data sources. Your work will enable the scalability and efficiency of our advanced analytics platform, helping our clients gain a holistic view of their marketing performance. You will be tasked with retrieving and consolidating diverse marketing data sources into the MarSci platform, enabling advanced analytics and actionable insights for our clients. This role involves understanding complex data ecosystems and working closely with stakeholders to continuously improve the platform’s functionality.

You will be responsible for the end-to-end process, including implementation, deployment, monitoring, and maintenance of data pipelines, while adhering to industry best practices in engineering and data management.

The project aims to revolutionize the digital analytics industry. Modern marketers face two major challenges: Where to allocate marketing investments and which marketing channel is effective. These challenges are driven by fragmented data sources, complex consumer journeys and lack of resources. MarSci aims to solve this by offering an integrated solution combining data visualization, cross-channel attribution (MTA), and media mix modelling (MMM). MarSci simplifies the use of advanced machine learning and AI for digital analytics, empowering marketers with actionable insights.

Main Responsibilities 

As part of the overall project, this Data Engineer will work on the following tasks:

Data Pipeline Development and Optimization: Design and maintain robust and scalable ETL pipelines to integrate and unify data from diverse sources, supporting MarSci’s advanced analytics and modeling needs. Optimize data pipelines to ensure high performance, reliability, and seamless processing for downstream applications.

• Data Quality and Security:

• Implement and maintain stringent measures to ensure data quality, integrity, and security across all pipelines.
• Proactively monitor and troubleshoot pipeline issues, implementing enhancements to improve stability and efficiency.

Collaboration with Machine Learning Teams:

• Work closely with machine learning engineers to prepare and structure data for advanced modeling, such as Multi-Touch Attribution (MTA) and Media Mix Modeling (MMM).
• Develop workflows that align with the unique requirements of AI-driven solutions within the MarSci platform.

Documentation and Usability:

• Create comprehensive documentation for data workflows and pipelines, ensuring accessibility and usability for technical and non-technical stakeholders.
• Develop user-friendly data solutions that empower teams to access and utilize data effectively.

Innovation and Scalability:

• Stay up-to-date with emerging technologies in data engineering, adopting cutting-edge tools and practices to enhance MarSci’s data infrastructure.
• Contribute to the strategic planning of scalable data architectures that align with MarSci’s long-term vision and innovation goals.

Agile Development:

• Employ Agile methodologies to iteratively build and refine data solutions, ensuring continuous delivery of impactful features.
• Actively participate in sprint planning to align short-term deliverables with the platform’s evolving objectives.

Administrative 

As a Data Engineer in Adapt, the person will occasionally be required to engage in administrative tasks in support of the PI and Commercial Leads overall activity. This may include drafting sections of reports for funding bodies; organising a programme of suitably themed group meetings and seminars; contributing to research funding proposals; drafting of ethics applications; and other such tasks as they arise.

Person Requirements

We are looking for an experienced Data Engineer capable of working with a multidisciplinary team to deliver the technology stack to deliver the MarSci innovation. Candidates with an interest in ETL process in digital analytics and advertising are particularly encouraged to apply

Qualifications
A primary degree in computer science, statistics or similar industry

Knowledge & Experience:
Essential:
A minimum of 3 years’ experience in a Data Engineer role;
Master’s or PhD in Computer Science or related field;
2+ years of experience in Data Engineer role, working with diverse data sources;
Experience with API integrations
Cloud infrastructure experience
Knowledge in test-driven development

Desirable:
Familiarity with data pipelines or working with diverse data sources

Skills
Essential:
Scalable Data Processes: Implement and manage scalable ELT (Extract, Load, Transform) pipelines and data architectures to handle complex data requirements.
Collaborate with cross-functional teams to gather data requirements and develop efficient solutions tailored to business needs.
Data Exploration and Insights: Conduct exploratory data analysis to identify patterns, trends, and opportunities within datasets.
Work proactively to uncover insights that can inform product development and strategic decision-making.
Continuous Improvement: Identify and execute opportunities for process optimization and enhancements in data operations.
Help shape the data roadmap for the domain by contributing to the strategic vision and prioritizing key initiatives.

Desirable
Very good understanding of digital analytics, media or advertising industry.
Industry Knowledge and Innovation: Stay informed about emerging industry trends, tools, and best practices in data engineering.
Leverage cutting-edge technologies to improve existing processes and ensure the platform remains at the forefront of innovation.
Knowledge of large language models (LLMs), fine-tuning methods, and prompt engineering to enhance model performance and align outputs with marketing analytics objectives.

Application Procedure
Applicants should email [email protected] providing the following information when applying:
1. A motivation statement outlining their interest and suitability for the position.
2. A comprehensive curriculum vitae
3. The names and contact details (e-mail) of three referees.
Note:
Candidates who do not address the application requirements above will not be considered for
an interview