Job description

Indent: PSL309127-2 Role: Senior Python Data Platform Engineer Location: Remote Max Rate : $ 70/hr 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.

Requirements

Must-haves

Indent: PSL309127-2
Role: Senior Python Data Platform Engineer
Location: Remote
Max Rate : $ 70/hr
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.

Nice-to-haves

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.

Application prep

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Keywords to mirror

pythongosqlgraphqlkubernetes

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