Data Architect

Who Are Massive Rocket? Massive Rocket is a rapidly scaling Braze and Snowflake agency on a mission to transform how digital marketing, product, and engineering teams connect. In just five years, we’ve grown at speed and are now gearing up for our next big milestone: hitting $100M in revenue. We build human experiences at scale, powered by cutting‑edge web, mobile, cloud, data, and AI technologies. If you’re excited by innovation, love solving complex challenges, and want to help shape the future of digital experiences, you’ll feel right at home here. Every role at Massive Rocket is entrepreneurial. The people who thrive here don’t just focus on their own remit — they understand the goals of the teams around them and actively contribute to the success of their colleagues, customers, and partners. We’re building a culture of ownership, collaboration, and growth, and we’re looking for people who want to make a real impact. Who Are We Looking to Add to Our Team? We’re looking for a Data Architect to help transform complex client requirements into scalable, data-driven solutions for global brands. You’ll lead technical discovery, design end-to-end data architectures, and shape roadmaps that connect customer data, identity, and marketing technology. Working closely with client stakeholders and our Data Engineering teams, you’ll combine deep technical expertise with strategic thinking to deliver robust architectures, improve data performance, and drive measurable business outcomes.

What Will You Do? Lead client discovery workshops to assess existing data platforms, identity frameworks, integrations, and business requirements. Design scalable data architectures integrating Snowflake, Databricks, mParticle, Hightouch, Braze, and wider MarTech ecosystems. Define data models, identity resolution, consent, governance, and data quality standards across multiple brands and markets. Develop technical roadmaps, scope delivery phases, estimate effort, and secure client approval before implementation. Evaluate data technologies and tools to ensure they meet business requirements, performance expectations, and commercial objectives. Guide Data Engineering teams in implementing and optimising data pipelines, including batch, event-driven, and low-latency data flows. Establish data validation, monitoring, performance optimisation, and engineering best practices. Translate complex data analysis and technical designs into clear recommendations and business value for client stakeholders. Mentor engineers and consultants, conduct technical reviews, and promote continuous improvement across delivery teams. Support proposals, pitches, workshops, and strategic initiatives while identifying opportunities to expand client engagements.