Data Engineer

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 an experienced Lead Data Engineer to design and deliver scalable, high-performance data solutions for our clients. You’ll lead data engineering initiatives, build and optimise data pipelines and models, and connect complex data sources to power analytics, customer engagement, and business decisions.

Working closely with Data, CRM, and CDP teams, you’ll bring strong technical expertise across modern data platforms, with a focus on Snowflake, SQL, Python, and dbt. You’ll also guide engineering best practices, explore new technologies and AI tools, and help clients get more value from their data infrastructure.

• Design, build, and maintain scalable ETL/ELT pipelines across batch and real-time data architectures.
• Develop and optimise data models, transformations, and workflows using SQL, Python, and dbt.
• Build and maintain integrations across cloud data platforms, warehouses, and external data sources
• Improve database performance, data reliability, and cost efficiency through monitoring and optimisation.
• Implement data quality checks, unit tests, and validation processes to maintain data integrity.
• Translate customer engagement and CRM data requirements into actionable data models and pipelines that power Braze and other platforms.
• Work with customer events, user attributes, identity resolution, and data synchronisation to support personalised customer experiences.
• Collaborate with Data, Analytics, CRM, and CDP teams to align technical solutions with client requirements and business goals.
• Provide technical leadership, guidance, and best practices to engineers and help drive continuous improvement.
• Identify opportunities to use AI tools, automation, and emerging technologies to improve engineering productivity and data workflows.
• Support multiple client engagements, communicate technical recommendations clearly, and adapt to changing priorities.
• Rocket‑Fuelled Growth – Big challenges, fast learning, and the chance to level up quicker than anywhere else
• A Culture That Actually Gives a Damn – Supportive, positive, and built around people who want to see you win
• A Global Crew – Collaborate with brilliant teammates across Europe, the US, and beyond
• Remote‑First for Life – Work from wherever you feel your best
• Real Career Momentum – Clear progression, real ownership, and space to grow into your next chapter
• Moments That Matter – Meetups, events, and team experiences that make the journey unforgettable

A Few Things to Know Before We Get Started

Bring Your Own Device – We operate a BYOD policy, so you’ll use your own kit for work

Right to Work – You’ll need a valid work visa; we’re not able to offer sponsorship at the moment

ID Checks – We may ask for proof of identity (passport, ID card, or a recent utility bill)

References – We may request two references, so have names, relationships, and contact details ready

For Contractors – Proof of incorporation and up‑to‑date insurance is required

A Quick Note on Applications

We receive a high volume of applications, and while we’d love to reply to everyone personally, it’s not always possible. If you haven’t heard from us within two weeks, it sadly means you haven’t been successful this time. But don’t let that stop you—we’re growing fast, and new opportunities open up all the time.

• 5+ years of experience in data engineering, data platforms, or a similar technical role, with strong ownership of architecture, implementation, and optimisation.
• 4+ years of hands-on experience with SQL, data modelling, and ETL/ELT processes.
• 2+ years of experience using Python to build data applications and transformations.
• Practical experience with dbt and modular data transformation.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud, and modern data integration tools.
• Strong understanding of data architecture, pipeline design, database performance, testing, and data quality.
• Experience translating business and customer engagement requirements into reliable data solutions.
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Experience working in an agency or consulting environment, managing multiple clients and adapting to changing priorities.
• A proactive approach to problem-solving, continuous learning, and using AI tools to improve day-to-day productivity.
• Ability to work independently while collaborating effectively with cross-functional teams.
• Strong written and verbal English communication skills (C1 level or equivalent).
• Hands-on experience with Snowflake, Hightouch, mParticle, or Databricks.
• Snowflake SnowPro Advanced: Architect or Data Engineer certification.
• Experience with customer data platforms (CDPs), identity resolution, audience activation, and real-time data synchronisation.
• Familiarity with Braze, CRM platforms, and customer engagement data models.
• Experience with other cloud data warehouses, such as BigQuery or Redshift.
• Knowledge of data visualisation tools such as Power BI or Tableau.
• Understanding of data governance, privacy, security, and access controls.
• Exposure to AI/ML architectures, cloud-native AI services, or agentic workflows.
• Experience working in Agile or Scrum environments.