Analytics Engineering Lead

About the company

At Redpin, our mission is to bring global citizens and businesses together by simplifying life’s most important payments.

Our world-class payments network and human-centric customer service touches a vast global community across 15,000+ partners, 235 territories and two flagship brands, Currencies Direct and TorFX. We are reshaping the age old property market by connecting the dots across the entire ecosystem, from buyers and sellers, to legal service firms and title companies to property management, banks and real estate agents.

Our goal is to become the leader in payments and embedded software for international property. We are a diverse team of over 800 employees across 10 offices worldwide, working together to connect the dots for hundreds of thousands of customers around the world.

By combining the brightest minds in global tech with our integrated portfolio of market-leading products and services, we are carving out a path to transform the global property market, making it faster, simpler and safer to buy property abroad.

About the role

We are building a cutting-edge data platform to help us simplify life’s most important payments. The Analytics Engineering Lead will lead a newly formed Analytics Engineering team responsible for the execution of a group-wide self-serve data strategy in collaboration with key stakeholders from across the organisation.

Reporting to the Senior Director of Data & AI, this person will be a credible, senior leader with the experience and impact to take us through the next phase of our data capability evolution. If you love to develop automated solutions to challenging business problems and craft game-changing insights with data, that change how an organisation operates, this is a role for you. We want you to bring your expertise with technology and experience in solving commercial problems into an environment where you’ll be working alongside other experts in both domains to scale our processes and make smarter decisions.

What you'll do…

• Lead and manage the Analytics Engineering team, providing technical guidance, mentorship, and fostering a culture of innovation and excellence.
• Design, develop, and maintain data models and ELT processes in a data mesh environment using dbt and Snowflake, ensuring scalability, reliability, and performance, adopting best practices, standards, and coding conventions.
• Collaborate with Insight Analysts, Data Scientists, and business stakeholders to understand analytical requirements and translate them into effective data solutions. Working across the organisation to identify opportunities to improve decision-making, designing and delivering solutions that make us smarter, quicker and faster.
• Implement and enforce data governance policies, including data quality, data lineage, and metadata management.
• Collaborate with the Data Engineering team to ensure the scalability, security, and availability of the overall Data Platform.
• Provide strategic guidance and contribute to the development of the overall data strategy. Identifying and evaluating new technologies, tools, and techniques to enhance the Analytics Engineering capabilities.

What you’ll need…

• You have a strong academic background in computer science, information systems, engineering, machine learning or other quantitative subject.
• You have strong commercial experience with SQL using MPP/EPPs such as Snowflake and BigQuery. Ideally modelling data with dbt in a data mesh environment.
• You’ve got experience in developing data reporting and BI solutions with self-serve capability in mind. You know how to shape requirements and work productively to achieve impact.
• You’ve got a keen eye for detail and are renowned for having high standards in your work
• You have experience in various data modelling techniques (3NF, Kimball, event data modelling).
• You’re the commercially-minded person in the engineering discussion and the person pointing out the technical considerations in the meeting of business people.

Our Data Stack

• Self-Serve Capability: Tableau / Sigma [incoming]
• Data Warehouse: Snowflake
• Data Modelling: dbt
• Cloud: AWS