Lead Enterprise Architect, Advanced Analytics

Job Title: Lead Enterprise Architect - Advanced Analytics
Location: Hybrid - London office in Southwark Bridge 2 days per week
Duration: 3 Months
Clearance: BPSS - Sole UK National
Rate: £650 per day - via Umbrella Only

Job description:
As the Lead Enterprise Architect for our Advanced Analytics business unit, you will lead the development of innovative tools and systems that power data-driven insights and analytics across the organisation. Your leadership will play a pivotal role in driving the next generation of advanced analytics capabilities, ensuring world-class performance, scalability, and efficiency.
This high-visibility role offers a broad scope of responsibility, where you'll influence the direction of our analytics solutions and shape the way we leverage data to optimise business outcomes.
You will work closely with passionate and dedicated colleagues and clients, all committed to driving transformation in the digital media space. Our open, innovative workspace fosters creativity and encourages new ideas, making it easy for everyone to contribute to our shared success.

What You'll Do:

Lead the development and enhancement of advanced analytics tools, focusing on data processing, integration, and optimization in a fast-paced, agile environment.
Manage, mentor, and grow a team of skilled engineers, providing guidance through regular performance reviews and career development opportunities.
Ensure seamless collaboration with cross-functional teams (product, engineering, business) to translate business objectives into actionable technical solutions.
Remove blockers and resolve technical challenges for engineering teams, ensuring smooth execution of analytics initiatives.
Actively participate in code reviews, design discussions, and ensure the implementation of best practices for scalable, future-proof solutions.
Champion agile methodologies, driving teams to deliver high-quality products on time and within budget.
Oversee the full SDLC (planning, design, development, QA, CI/CD, and production support) to ensure timely and efficient delivery of analytics solutions.
Provide second-level support for production systems, ensuring the stability, reliability, and performance of analytics platforms.
Collaborate with architects and other engineering leaders to establish standards, process documentation, and conduct impact assessments.
Manage and resolve escalations effectively, ensuring smooth operations and minimal disruption to project timelines.
What You'll Need:

3+ years of experience in a leadership role with 5+ years of hands-on software engineering experience.
Strong expertise in software architecture, data pipeline design, and scalable analytics systems.
Proven experience with integrating and automating business workflows, including data-driven processes and system integrations.
Familiarity with analytics platforms and tools such as GCP (BigQuery), AWS (Glue, Athena), or Azure Databricks.
Proficiency in Python or .NET, with experience in both or the ability to quickly learn new technologies.
Experience with front-end frameworks (Angular/React) and back-end development (API management, microservices).
Strong knowledge of SQL, data modelling, and database optimization techniques.
Hands-on experience with Docker, cloud platforms (GCP, AWS, Azure), and CI/CD pipelines.
Familiarity with event-driven architectures and building real-time data analytics solutions.
Experience working with large-scale, high-concurrency systems and ensuring high availability.
Previous experience managing globally distributed teams, fostering collaboration across time zones.
Experience in building machine learning solutions and data-driven software is a plus.
You Have a Passion For:

Solving complex data challenges and turning raw data into actionable business insights.
Collaborating with business stakeholders to identify analytics opportunities and optimise business processes.
Innovating and developing solutions that drive data efficiency and performance.
Leading teams with empathy, recognising gaps in knowledge and proactively pursuing development opportunities.
Agile development practices, continuous integration, automation, and delivering high-quality analytics solutions.
Communicating effectively with business users, product managers, and senior leadership to ensure alignment on objectives and technical strategies.
Working in fast-paced, entrepreneurial environments, particularly in data-driven or analytics-heavy industries