Staff Data Engineer
Big Data
Bigdata
Cloud
Cloud Data Warehouse
Cloud Platform
Cloud Platforms
Data
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Engineering
Data Governance
Data Integration
Data Management
Data Modeling
Data Operations
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Security
Data Warehouse
Data Warehousing
Database
Databases
Databricks
Engineer
ETL
Google Cloud Bigquery
Reporting and Analytics
Snowflake
Spark
SQL
Job Description
Staff Data Engineer role focused on leading the architecture and reliability of a company-wide data platform.
Responsibilities
- Own the target-state data architecture across ingestion, modeling, semantic layer, and serving, including a sequenced roadmap and explicit trade-offs
- Lead build vs. buy and tooling choices for ingestion, transformation, orchestration, and observability
- Own data trust by making freshness, correctness, and lineage observable; enforce standards through CI
- Maintain a single definitional layer so the same metric is consistent across systems like BigQuery, HubSpot, and board decks
- Build governed foundations for AI features, including identity resolution and canonical entity models
- Lead and grow the data engineering team while staying close to the code for review of hard designs and complex queries
Requirements
- 8+ years in data engineering with experience serving as an architect of a cloud data platform (not just execution or contribution)
- Strong hands-on fluency with BigQuery (or Snowflake/Databricks), dbt, Python, and advanced SQL
- Production experience shaping real decisions on orchestration, idempotency, and testing, driven by incident response and on-call
- Experience leading engineers formally or as a technical lead, comfortable in a player-coach role
- Design mindset that treats access control, PII handling, and auditability as core requirements
Technologies
- BigQuery, Snowflake, Databricks
- dbt
- Python
- SQL
- HubSpot
Nice to Have
- Marketing attribution or multi-touch modeling across CRM, product, and clickstream data
- Experience building data foundations for ML or LLM-based product features
- Background in legal, healthcare, or fintech, or early data hire experience at a high-growth company
Location
- New York, NY (onsite)
- In-person at the NYC office 5 days per week
Compensation
- USD 250,000 - 300,000 per year
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