Rockstar
Helping rockstar candidates get introduced to their next role.
Founding Staff Engineer
Location
North Carolina
Posted
48 days ago
Salary
Not specified
Bachelor Degree10 yrs expEnglishETLPythonSQLType Script
Job Description
• Build full-stack product features end-to-end: frontend UI, backend APIs/services, data pipelines, deployment and observability.
• Own the integration strategy and connector architecture across multiple vendors and authentication patterns (OAuth/API tokens/read-only portal access/automated exports).
• Design and implement data ingestion and processing primitives: retries, idempotency, backfills, schema evolution, and anomaly detection.
• Create a flexible canonical data model and mapping layer that can normalize structural + semantic differences across systems (e.g., different definitions of revenue/net sales/business day).
• Build the metrics/semantic layer that powers product experiences and deterministic tool outputs (numbers must be correct and auditable).
• Implement data quality and validation workflows so failures are observable and fixable (quarantine/error surfacing instead of silent wrongness).
• Make sound build vs buy recommendations for integration tooling and infrastructure (unified APIs, managed ETL, warehouses, observability, etc.).
• Work directly with the founder and pilot partners to unblock access issues, validate data, and iterate quickly.
Job Requirements
- 10+ years building production software; prior Staff/Principal level or equivalent.
- Proven full-stack ownership: you can ship UI + backend + data pipelines without needing separate specialists.
- Strong TypeScript experience (frontend and backend); Python experience is a plus (not required).
- Deep experience with data engineering fundamentals: SQL, modeling, ETL/ELT, event-driven ingestion, reconciliation/validation, and operationalizing pipelines.
- Experience building and maintaining multiple third-party integrations (API design, rate limits, auth, retries, monitoring, vendor quirks).
- Strong systems design judgment: you choose tools/architecture based on constraints and tradeoffs, not familiarity.
- Comfortable operating in ambiguity with real customers and aggressive timelines.
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