Senior Backend Engineer, Data

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Develop and sustain Databricks and PySpark data pipelines utilizing a medallion-style Bronze/Silver/Gold architecture.

• Establish data quality checks, enforce schema, and track data lineage.

• Design and enhance ETL/ELT workflows for large-scale marketing performance data.

• Collaborate with analytics and data science teams to create clean, well-structured data assets.

• Create backend services and APIs in Python using FastAPI, Flask, or similar frameworks.

• Implement microservices, domain boundaries, caching strategies, and queuing patterns.

• Facilitate service-to-service communication through REST, gRPC, and event-driven patterns.

• Integrate with external marketing platforms, cloud services, and internal microservices.

• Enforce authentication, authorization, rate limiting, and multi-tenant access controls.

• Produce production-ready code, engage in code reviews, and guide engineers through technical mentorship.

• Develop and maintain CI/CD pipelines and infrastructure-as-code environments.

• Implement tracing, structured logging, metrics, and alerting systems.

• Optimize services for latency, concurrency, throughput, and cost-effectiveness.

• Contribute to automated testing, load testing, and resilience practices.

• Collaborate with SRE on SLIs/SLOs and partner with product, data, and SRE teams for backend design.

⛳️ Requirements

• Minimum of five years of experience in backend engineering, data engineering, or distributed systems.

• Strong practical expertise in Python, with experience in FastAPI, Flask, or comparable modern backend frameworks.

• In-depth proficiency with Databricks and PySpark, including hands-on experience with medallion-style data architecture, or a strong willingness and capability to learn quickly.

• Comprehensive understanding of microservices, concurrency, asynchronous programming, and event-driven architectures.

• Proficient in SQL and NoSQL databases, such as PostgreSQL, DynamoDB, Redis, MongoDB, or similar technologies.

• Familiarity with lakehouse platforms.

• Practical experience with Docker, Kubernetes, and AWS.

• Experience with infrastructure-as-code tools like CloudFormation.

• Strong CI/CD experience with GitHub Actions, Argo, or similar tools.

• Solid understanding of observability practices, including logs, metrics, traces, and performance analysis.

• Proven track record of producing clean, testable, and well-structured production code.

• Proficient in English, both spoken and written.

• Familiarity with AI/LLM systems and agentic workflow integration is advantageous.

• Experience with Kafka, Pub/Sub, or SQS is a plus.

• Familiarity with Delta Lake, Unity Catalog, or other lakehouse governance and optimization tools is advantageous.

• Previous experience with API gateway architectures, caching layers, or service meshes is a plus.

• Familiarity with marketing, advertising, or platform APIs is a plus.

🏝️ Benefits

• Opportunities for continuous learning and knowledge sharing.

• A company culture focused on diversity and inclusion.