Senior Backend Engineer, Data
Posted 8hrs ago
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Job Description
Senior Backend & Data Engineer building Python services and Databricks/PySpark pipelines for Publicis Groupe’s marketing intelligence platform. Supporting distributed systems, analytics, and campaign automation.
Responsibilities:
- Build and maintain Databricks and PySpark data pipelines using medallion-style Bronze/Silver/Gold architecture, data quality checks, schema enforcement, and lineage tracking
- Build and optimize ETL/ELT workflows for large-scale marketing performance data
- Collaborate with analytics and data science teams on clean, well-modeled data assets
- Build backend services and APIs in Python using FastAPI, Flask, or equivalent frameworks
- Implement service-to-service communication using REST, gRPC, and event-driven patterns
- Integrate with external marketing platforms, cloud services, and internal microservices
- Implement authentication, authorization, rate limiting, and multi-tenant access controls
- Write production-ready code, participate in code reviews, and mentor engineers through technical influence
- Build and maintain CI/CD pipelines and infrastructure-as-code environments
- Implement tracing, structured logging, metrics, and alerting
- Optimize services for latency, concurrency, throughput, and cost efficiency
- Contribute to automated testing, load testing, and resiliency practices with SRE
- Collaborate with product, data, and SRE teams on backend designs across campaign activation domains
Requirements:
- At least 5 years of experience in backend engineering, data engineering, or distributed systems
- Meaningful contributions to the design of services or pipelines
- Strong hands-on expertise in Python and modern backend frameworks such as FastAPI or Flask
- Strong hands-on proficiency with Databricks and PySpark
- Practical experience with medallion-style Bronze/Silver/Gold data architecture, or strong willingness and aptitude to learn it quickly
- Understanding of microservices, concurrency, asynchronous programming, and event-driven architectures
- Proficiency with SQL and NoSQL databases such as PostgreSQL, DynamoDB, Redis, or MongoDB
- Familiarity with lakehouse platforms
- Hands-on experience with Docker, Kubernetes, and AWS
- Experience with infrastructure-as-code tooling such as CloudFormation
- Strong CI/CD experience with GitHub Actions, Argo, or similar tools
- Working knowledge of observability practices including logs, metrics, traces, and performance analysis
- Ability to write clean, testable, well-structured production code
- Fluent English, verbal and written
- Familiarity with AI/LLM systems, streaming or queuing systems, Delta Lake, Unity Catalog, API gateways, caching layers, service meshes, or marketing and advertising APIs would be advantageous

















