Senior Data Platform Engineer
New
P
PushPressFitness software
Listing location: USA; Workplace type: RemoteFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years in data engineering, data platform, data infrastructure, or software engineering roles
- Required Skills
- PythonSQLAirflowClickhouseTerraform
Requirements
- Bring 5+ years of experience in data engineering, data platform, data infrastructure, or software engineering.
- Have owned production infrastructure end to end.
- Have experience with a cloud warehouse at scale, including performance tuning, cost management, access controls, and schema design.
- Demonstrate strong Python and SQL skills and software engineering practices such as testing, CI/CD, code review, and infrastructure as code.
- Have hands-on production experience initiating, maintaining, and operating an orchestrator such as Airflow or Dagster.
- Have experience with managed ingestion tools such as Hevo or Fivetran and custom pipelines, including CDC, streaming, or event-driven data.
- Have built data quality checks and alerting, with a runbook others can follow.
- Use AI daily, including at least one workflow others rely on and a check that catches errors.
- Have experience with a real-time analytics database such as ClickHouse and know when to use it instead of a warehouse.
- Have worked with privacy and governance requirements under GDPR, CCPA, or PCI.
- Be familiar with TypeScript codebases and product engineering teams.
Responsibilities
- Make PushPress reporting fresh, fast, and accurate, and ensure company metrics trace back to their sources.
- Set data freshness and uptime standards, participate in incident response, and fix root causes.
- Bring product, payment, and third-party data together to represent the customer journey.
- Partner with Engineering so features and integrations produce well-structured data and breaking changes are caught before release.
- Simplify data movement, clarify tool ownership, and monitor costs.
- Protect gym and member data with access controls, access records, and safeguards for AI systems.
- Support privacy requests while preserving financial reporting and audit requirements.
- Provide context and readable business definitions for AI Assistant, AI Member Intel, and AI reporting.
- Help teams answer questions through AI with clear limits on cost and access.
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