Staff Data Engineer

Manifest OS; New York (NY); On-site; USD 250,000 - 300,000; Full time

Job summary

Manifest OS, located in New York, seeks a Staff Data Engineer to own and direct the architecture and direction of the data platform. This in-person role leads a team in NYC and focuses on scalable data solutions for analytics and AI foundations.

The role requires 8+ years of data engineering with architecture leadership, fluency in BigQuery/Snowflake/Databricks, dbt, Python and advanced SQL. You will guide trade-offs, governance, and team growth in a hands-on leadership capacity.

Qualifications

• 8+ years of data engineering and architecture of a cloud data platform.
• Hands-on fluency with BigQuery, Snowflake or Databricks, dbt, Python and advanced SQL.
• Production experience with orchestration, idempotency and testing best practices.
• Experience leading engineers in a formal or technical-lead role.
• Design requirements include access control, PII handling and auditability.

Responsibilities

• Own target-state data architecture with a sequenced roadmap and trade-offs.
• Drive build-versus-buy decisions across ingestion, transformation, and observability.
• Ensure data freshness, correctness, lineage, and CI-driven standards.
• Maintain a single definitional layer for consistent metrics across sources.
• Build governed foundations for AI features including identity resolution and canonical models.
• Lead and grow the team while reviewing hard designs and complex queries.

Skills

Leadership

Architectural leadership

Advanced SQL

Tools

BigQuery

Snowflake

Databricks

dbt

Python

SQL

HubSpot

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