Senior Data Platform Engineer

Role Overview

Senior Data Platform Engineer responsible for building and evolving a modern data platform that powers product and business decisions at scale. You’ll own core infrastructure across ingestion, orchestration, observability, and transformation—balancing operational stability with long-term architectural evolution.

Responsibilities

• Own and evolve data platform infrastructure across ingestion, transformation, orchestration, and observability
• Build, maintain, and modernize core data systems for product, analytics, and engineering workflows
• Drive platform reliability through improved monitoring, alerting, incident response, and reduced operational toil
• Partner with engineering and data stakeholders to translate platform needs into scalable system designs
• Contribute to long-term architecture: modernization and migration of legacy systems
• Develop and maintain Python-based tooling for pipelines, automation, and data quality enforcement
• Apply DevOps/SRE practices to ensure uptime, performance, and operational excellence
• Mentor engineers and help define best practices for reliability, documentation, and system design

Requirements

• Strong background as a data platform or backend engineer across infrastructure, data engineering, and reliability
• 4–6+ years experience in data engineering, backend engineering, DevOps, or SRE
• Strong proficiency in Python, building production-grade systems and tooling
• Experience with data platforms/tools such as Snowflake, dbt, Spark, or similar
• Familiarity with cloud infrastructure (AWS preferred) and distributed systems concepts
• Understanding of observability, monitoring, and production reliability practices
• Ability to work across legacy systems while driving incremental modernization
• Strong systems thinking and ability to balance short-term execution with long-term architecture
• Collaborative mindset and strong communication in ambiguous environments

Nice to Have

• Experience with Kubernetes
• Experience with data observability tools
• Experience with ML infrastructure

Benefits / Work Model

• Fully remote-first with distributed teams
• Employer-covered healthcare (100% for employees; partial for dependents)
• Generous parental leave and mental health support
• Home office/co-working/internet/professional development stipends
• Unlimited paid time off
• Mission-driven culture with learning and autonomy