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.

At least ten years of experience in backend, data platform, or distributed systems, including ownership across multiple services or teams.
Expertise in Python, API design, service boundaries, async and concurrent systems, SQL, and modern testing practices.
Proficiency with Databricks, PySpark, Lakehouse patterns, and medallion-style data architecture, or equivalent large-scale data pipeline experience.
Strong AWS serverless experience, including Lambda, API Gateway, S3, DynamoDB, IAM, and CloudFormation/SAM or equivalent infrastructure-as-code tooling.
Deep understanding of multi-tenant SaaS design, authentication and authorization, tenant-scoped data access, secrets management, and operational security.
Experience designing stable data contracts, CLI/API/MCP contracts, schema evolution patterns, and consumer-facing data models.
Proficiency with SQL and NoSQL databases such as PostgreSQL, DynamoDB, Redis, or MongoDB.
Strong CI/CD experience and deep knowledge of observability practices including logs, metrics, and traces.
Proven technical leadership through mentoring, architecture decisions, code reviews, trade-off communication, and engineering standards, without relying on direct authority.
Fluent in English, both verbal and written.

Principal Data Engineer, Backend

Key skills