We are looking for a Senior Lifecycle Platform Engineer (Pipeline-First) to join an embedded, outcome-focused engineering team. This track prioritizes production-grade Python pipeline engineering, observability, and automation fundamentals over domain-specific ESP platform experience.
The core mission: replace fragile, manual campaign execution workflows with reliable, observable, automated systems, and harden the messaging infrastructure that powers email and SMS at scale for tens of millions of users.
The client's Engineering Manager will retain ownership of ESP and Iterable architectural decisions. The engineer in this track will own the pipeline layer: audience selection, automation, observability, and production reliability. ESP onboarding (Iterable) will be covered in the structured 30-60-90 plan.
Responsibilities:
- Design and build production-grade Python pipelines that automate lifecycle campaign execution (SMS reactivation, email sequences, audience segmentation).
- Engineer SQL-driven audience selection logic, segmentation, suppression, and consent/DNC compliance using BigQuery or equivalent data warehouse.
- Integrate predictive model outputs (from the data science team's ML models) into the messaging pipeline, wiring model scores to control send volume and targeting decisions.
- Build full observability across all messaging pipelines using Datadog, early alerting, dashboards, and SLO monitoring before failures affect ad spend or budgets.
- Work at the API level with Iterable (or equivalent ESP) to configure campaign triggers and data pipelines, with ramp-up support from the Engineering Manager.
- Configure and wire backend data for new email templates (RTA, Discovery layouts), pulling property data into ESP templates for A/B testing.
- Eliminate throughput bottlenecks and daily congestion alerts across the messaging platform.
- Drive cross-channel messaging consistency across email, push, and SMS, ensuring unified messaging logic from a single orchestration layer.
- Translate business campaign requirements from non-technical marketing stakeholders into technically sound, compliant production pipelines.
- Maintain and make targeted changes to an existing Rails 8 messaging orchestration service as needed.
What We Are Looking For:
Core Requirements (all must be demonstrated from production experience):
- Strong Python — data pipeline context. This is the primary gate. Airflow DAGs, pipeline scripts, BigQuery integrations, operational automation. NOT web framework Python. Django/FastAPI-only backgrounds do not qualify.
- Production-grade pipeline engineering. Demonstrated experience building and operating data pipelines in production: scheduling, dependency management, failure handling, retry/backoff, idempotency, and monitoring. Airflow is preferred; equivalent tools (Prefect, Luigi, etc.) are acceptable.
- SQL with any major data warehouse. Strong SQL skills applied to audience selection at scale, segmentation logic, and data transformation. BigQuery, Redshift, Snowflake, or equivalent.
- Observability mindset. Datadog (or equivalent) instrumentation, alerting, and dashboard experience. You understand downstream consequences of silent failures and proactively instrument systems.
Also Required:
- 6+ years of backend or platform engineering in production environments.
- Lifecycle compliance awareness: unsubscribe management, consent controls, DNC exclusions (can be learned; domain exposure is a plus).
- Idempotency patterns, resilient API integrations.
- Ability to work autonomously with non-technical marketing stakeholders.
- Comfort reading and navigating an existing codebase in an unfamiliar language (Ruby on Rails 8 — changes will be targeted and minimal).
Required Soft Skills:
- Proactivity — Do not churn silently on blockers. Reach out early, surface issues before they compound, and take initiative without waiting to be asked.
- Over-communicate — Post status updates in team channels, document what you're working on, what you completed, and what's blocking you. Make your presence felt.
- Be loud — Speak up in channels, flag risks, share progress. Visibility is valued over quiet heads-down work in this team culture.
- Open to hop on a call — When async communication isn't cutting it, jump on a huddle or quick video call to work through technical issues or nail down business requirements.
- Testing & tedious resiliency — Many changes will be small, incremental, and iterative. The team must protect existing revenue while iterating. A candidate who needs big, greenfield projects to stay motivated is the wrong fit.
Nice to Have:
- ⭐ Strong nice-to-have: ESP API experience — Iterable, Braze, Klaviyo, Salesforce Marketing Cloud, or equivalent. ESP onboarding on Iterable is built into the 30-60-90 plan, but prior ESP API experience is a meaningful differentiator between otherwise equal candidates and significantly accelerates ramp-up.
- BigQuery (preferred data warehouse; not required if SQL fundamentals are strong).
- Apache Airflow production experience.
- SendGrid, Commio, Twilio, and/or AppsFlyer.
- Template data personalization (pulling property data into email templates for personalization).
- Sidekiq or similar background job processing.
- Google Cloud Pub/Sub, Redis.
- Multi-platform messaging consolidation experience.
- B2C consumer tech background (proptech, marketplace, rental, rideshare).
What This Role Is Not:
- Not a Python web framework role — Django/FastAPI alone does not qualify.
- Not an ESP gate — Iterable, Braze, Klaviyo experience is a nice-to-have, not a requirement. ESP onboarding is built into the 30-60-90 plan.
- Not a Rails-first role — Rails familiarity is helpful; Rails expertise is not required.
- Not a generic ETL/warehouse role — data warehousing and pipeline skills are core, but the candidate must also demonstrate experience with operational automation, API-driven integrations, and production reliability. Pure batch data transformation without those layers is not sufficient.
- Not a marketing automation specialist — this is a software engineering role.
- Not a trigger architecture redesign — the current profile-field-based email triggers work and the business has explicitly deferred rebuilding them as API-event-based triggers.
