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?

As a Data Quality Engineer, you'll be the guardian of trust in our customer data ecosystem — profiling, validating, and monitoring data across pipelines to make sure what lands in our platforms is accurate, complete, and ready for activation.

You'll work across data, Martech, and engineering environments, digging deep into datasets with advanced SQL, building Python-based validation and monitoring frameworks, and testing everything from customer data pipelines and identity resolution to SDK events, APIs, CDP integrations, and downstream activation in platforms such as Databricks, mParticle, Braze, and OneTrust.

This is a hands-on, data-first engineering role. You'll spend as much time profiling and interrogating data as you do writing code — building the frameworks, checks, and monitors that catch issues before they reach the business. You'll work closely with Data Engineers and Martech teams to identify issues early, prevent regressions, and ensure customer data is accurate, compliant, and ready for activation.

Please note this role is part time (Monday / Tuesday / Wednesday half day)

What Will You Do?

• Profile large, complex datasets using advanced SQL to uncover anomalies, inconsistencies, duplication, and drift before they become production issues
• Build automated data quality and testing frameworks from scratch to validate customer data, schemas, data contracts, and identity resolution across the data ecosystem
• Design and maintain automated test suites tailored specifically to data pipelines — not general application testing — covering batch and near real-time flows
• Test end-to-end ETL/ELT pipelines across platforms such as Databricks, mParticle, Braze, and OneTrust, including API integrations and audience activation
• Validate data transformations, freshness, and latency against defined SLAs, and build monitoring to catch schema drift and corrupted records early
• Use Python and SQL together to automate regression testing, anomaly detection, and large-scale dataset validation
• Develop automated tests for web and app events, SDK implementations, consent signals, and customer journeys
• Build API mocks and automated integration tests to ensure data and customer actions flow correctly between systems
• Partner closely with Data Engineers and Martech teams to triage defects, identify root causes, and prevent recurring data quality issues
• Embed automated data quality checks into CI/CD workflows and continuously improve the testing and monitoring architecture
• Validate consent and preference management across customer data flows to support GDPR, UK GDPR, and other privacy requirements