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
Manifest OS is seeking a Staff Data Engineer to own and direct the architecture, reliability, and direction of the company data platform, while leading the team that builds it. This is an in-person role based in the NYC office, five days per week.
Role Focus
You will lead the target-state data architecture end to end, including ingestion, modeling, the semantic layer, and serving. You will set sequencing and document trade-offs for key decisions, ensuring the platform supports both day-to-day analytics and governed foundations for AI features.
Responsibilities
- Own the target-state data architecture covering ingestion, modeling, semantic layer, and serving, including a sequenced roadmap and named trade-offs
- Drive build-versus-buy and tooling decisions across ingestion, transformation, orchestration, and observability
- Own data trust by making freshness, correctness, and lineage observable and enforcing standards through CI
- Maintain a single definitional layer so metrics have consistent meaning across BigQuery, HubSpot, and board decks
- Build governed foundations for AI features, including identity resolution and canonical entity models
- Lead and grow the team while staying close enough to review hard designs and complex queries
Required Qualifications
- 8+ years of data engineering, including serving as an architect (not only a contributor) of a cloud data platform
- Hands-on fluency with BigQuery (or Snowflake/Databricks), dbt, Python, and advanced SQL
- Production experience where opinions on orchestration, idempotency, and testing came from being paged
- Experience leading engineers formally or as a technical lead, with comfort in a player-coach role
- Ability to treat access control, PII handling, and auditability as core design requirements
Technologies
BigQuery, Snowflake, Databricks, dbt, Python, SQL, HubSpot
Nice-to-Haves
- 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; early data hire experience at a high-growth company
Work Location and Compensation
- Location: New York, NY (onsite)
- Schedule: In-person, 5 days per week
- Compensation: USD 250,000 - 300,000 per year
- Minimum Experience: 8 years
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