About this role
Job title: Senior Software Engineer – Microservices and Data Pipelines
About the Role Senior Software Engineer – Microservices and Data Pipelines at Zeta Global is part of the Data Connectivity POD, building and operating data platforms that handle inbound and outbound data flows across batch and streaming pipelines on AWS with Iceberg tables. You will build scalable, self-service data pipelines and connector frameworks for enterprise-scale data products, enabling real-time insights and personalized experiences.
What You'll Do
- Design, implement, and operate Python-based microservices and high-throughput ETL pipelines that meet enterprise SLAs, RPO/RTO targets, and data quality standards.
- Embed observability by default through structured logging, metrics, and distributed tracing; define SLOs, error budgets, and incident response runbooks for production services.
- Design and evolve reusable connector frameworks for inbound and outbound integrations with Ad tech platforms like Facebook Ads, Google Ads, and other enterprise systems, emphasizing modularity, versioning, and backward compatibility.
- Collaborate with Product, SecOps, and Platform teams to deliver scalable, cost-efficient solutions across Kubernetes, message buses, and workflow orchestrators.
What We're Looking For
- 5+ years in backend/data engineering building Python services and ETL pipelines for enterprise environments with strict uptime, compliance, and performance requirements.
- Expert Python skills, including async I/O, concurrency, and service frameworks, plus strong testing strategies, and interface contracts for maintainability at scale.
- Proven microservices experience with containers and orchestration and event-driven patterns using message brokers or streaming platforms.
- Robust SQL skills integrating with analytics warehouses such as Snowflake, including cost/performance tuning patterns.
- Production-grade integrations with APIs, including rate-limit handling, retries, backoff policies, and change-data capture or incremental sync designs.
- Deep observability practice using metrics, logs, and traces and experience implementing Open Telemetry instrumentation and alerting workflows.
Nice to Have
- Experience leveraging Apache Spark for efficient processing and management of large-scale distributed data workloads.
- Strong understanding of modern Lakehouse architectures that unify data lakes and warehouses.
- Exposure to serverless data patterns.