LURECRUITER
Senior Data Platform Engineer (Python, Airflow)
Rol remoto de Senior Data Platform Engineer con fit claro de ubicación del candidato.
Publicado20 jun 2026
Países elegibles25 países aceptados
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Resumen del rol
Senior Data Platform Engineer (Python, Airflow)
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
What You Will Work On
- Design and build production-grade Python pipelines (Airflow DAGs) that automate lifecycle messaging workflows end-to-end.
- Replace manual processes (audience prep, segmentation, suppression, send execution) with reliable, scheduled, testable systems.
- Engineer SQL-driven audience selection logic at scale (BigQuery or equivalent) Segmentation, suppression lists, consent/DNC compliance, and idempotency patterns to prevent double-sends.
- Build observability across messaging pipelines (Datadog or equivalent) Instrument pipelines with alerts, dashboards, and monitoring to catch failures before they impact spend or delivery
- Integrate machine learning model outputs into pipeline workflows Use model scores to control send volume, targeting, and campaign decisioning
- Work with Iterable (or equivalent ESP) at the API level Configure campaigns, triggers, and data flows programmaticallyESP onboarding support is provided — prior ESP experience is a plus, not required
- Configure backend data for dynamic email templates Wire property data (name, ID, images, attributes) into templates to enable personalization and A/B testing
- Standardize messaging logic across channels (email, SMS, push) Unify trigger thresholds and decisioning across systems
Core Requirements
- Strong Python in a data pipeline context Airflow DAGs, pipeline scripting, automation, data integrationsNot web frameworks (Django/FastAPI/Flask)
- Production pipeline engineering experience Scheduling, dependency management, failure handling, retries, idempotency, monitoring
- Airflow (or equivalent orchestration tools) Prefect, Luigi, or similar tools are acceptable
- Strong SQL + data warehouse experience BigQuery preferred; Snowflake/Redshift acceptable Experience with large-scale audience segmentation and data transformations.
- Observability mindset - Experience with Datadog or equivalent monitoring tools.
- 6+ years of backend or platform engineering in production environments.
- Fluent English.
Nice to haves
- ESP API experience (Iterable, Braze, Klaviyo, Salesforce Marketing Cloud, etc.)
- Messaging infrastructure experience (email/SMS/push systems)
- Experience integrating ML model outputs into production systems
- Background in B2C or marketplace platforms
What This Role Is NOT
- Not a Python web development role
- Not a pure data engineering role (ETL-only profiles are not a fit)
- Not a marketing automation specialist role
Why You Should Apply
- Remote — work from anywhere in Latin America
- USD compensation
- Paid time off
- High-impact role — own systems that power messaging at massive scale
- Work on real production systems from day one
- Strong learning and growth opportunities in pipeline engineering and platform systems
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