Description

Job Description

Role:

Overview

We are seeking an experienced Senior Python Data Platform Engineer to complete and productionize a critical event-streaming service that powers customer activity data across Segment, Snowflake, Salesforce, Amplitude, Inflection, and other GTM platforms.

The role involves taking ownership of an existing partially completed Python service, migrating a legacy Kafka-based integration to the company's Eventing Platform, improving data quality, validating downstream integrations, and delivering a fully operational solution with documentation and knowledge transfer.

Key Responsibilities

• Assess existing Go and Python codebases and define the productionization plan.
• Complete development of a Python-based Eventing Platform to Segment service.
• Implement production-grade error handling, retries, dead-letter queues, monitoring, alerting, and structured logging.
• Perform event inventory, schema validation, and field-level parity analysis.
• Configure and validate Segment destinations, including Inflection, Snowflake, Salesforce, and Amplitude.
• Address data quality issues, including customer segmentation and user-level attribution.
• Execute end-to-end testing, reconciliation, and production validation against the legacy pipeline.
• Support cutover, rollback planning, legacy service decommissioning, and operational handoff.
• Produce architecture documentation, runbooks, and knowledge-transfer sessions for internal teams.

Required Skills & Experience

• 10+ years of software engineering experience.
• Strong hands-on Python development experience in production environments.
• Experience building and operating event-driven and streaming systems.
• Strong Kafka knowledge and experience with pub/sub architectures.
• Experience with Protobuf schemas, schema evolution, and event versioning.
• Experience with Segment or similar Customer Data Platforms (CDPs).
• Working knowledge of Go sufficient to understand and analyze existing code.
• Strong SQL and Snowflake experience for data validation and reconciliation.
• Experience with monitoring, observability, and operational support of distributed systems.
• Proven experience taking over unfinished projects and successfully delivering them to production.
• GraphQL clients for enriching events from internal data services
• TLS/mTLS for service-to-service auth
• Kubernetes or equivalent container platform (health checks, rollouts, resource tuning)

Preferred Skills

• Experience with Segment destination configuration.
• Knowledge of Inflection, Salesforce, Amplitude, or similar MarTech platforms.
• Marketing, customer engagement, or GTM data experience.
• Experience working in large monorepos and enterprise engineering environments.
• Strong technical documentation and knowledge-transfer capabilities

Key Skills

Education

Any Graduate