jaydhub

Data Engineer

• Own backend and data architecture across marketing data pipelines, connector systems, platform APIs, agent/tool runtimes, and downstream product surfaces, defining durable domain boundaries and data contracts between warehouse outputs, platform APIs, agent tools, and user-facing workflows.
• Turn ambiguous platform needs into incremental technical plans that balance reliability, security, tenant isolation, developer experience, and long-term maintainability.
• Lead the evolution of data pipelines following the medallion architecture, driving data quality, schema enforcement, lineage, and curated outputs for analytics and product use cases.
• Harden ingestion from external marketing platforms and related APIs, including connector and reconciliation patterns.
• Architect backend services across API paths and cloud infrastructure, shaping how platform capabilities are exposed through stable contracts, streaming workflows, and tool permissions.
• Implement secure authentication, authorization, rate limiting, and multi-tenant access controls across services.
• Write high-quality, production-ready code and integrate with external APIs, cloud services, and internal microservices.
• Build and maintain deployment pipelines and infrastructure environments, implementing tracing, structured logging, metrics, and alerting to ensure reliability, latency, and operational standards.
• Mentor engineers, contribute to internal libraries, backend frameworks, and drive consistency across the platform.

Principal Data Engineer

Product Manager

• Get up to speed quickly on the existing products, understand what has been built, what is in progress, and what is planned, and become the person who holds that context.
• Work closely with the Business Product Manager to capture business requirements and translate them into structured technical specifications the engineering team can act on.
• Own the Product Backlog, define, prioritize, and refine items with clear work breakdown structures, estimates, and acceptance criteria.
• Manage dependencies across teams, track delivery progress, and proactively communicate risks and blockers to stakeholders.
• Build and maintain product roadmaps that align upcoming features and initiatives with delivery capacity.
• Pick up ongoing features and initiatives already in production and ensure they work.
• Serve as the day-to-day link between the engineering teams and the business side, keeping both aligned and unblocked.
• Support the team in progressively introducing structured practices and delivery processes as the organisation scales.

SDET

• Audit the current state of QA across all development teams, identify gaps, and build a clear automation roadmap with concrete goals and milestones.
• Design and implement automation frameworks and quality gates that teams can adopt and run independently, without requiring QA involvement for every release.
• Act as the reference for QA standards and practices, enabling teams to self-serve, raise the quality, and integrate quality checks into deployment pipelines.
• Define and track QA metrics such as test coverage, defect rates, and release quality, and use them to drive continuous improvement across teams.
• Evaluate new AI and automation approaches regularly and bring forward the ones that will have the most impact.

Principal Data Engineer

Product Manager

QA Automation Lead