Principal Engineer

VaynerX•New York, NY

10d•$180,000 - $195,000

About The Position

VaynerX Connected Systems team builds and operates the data platform that connects our core business systems into a unified Snowflake data warehouse, using modern cloud and transformation tooling. We're looking for a Principal Engineer to take ownership of platform delivery, raise the technical bar across the team, and bring deep expertise in integrating diverse and complex data sources. You'll work closely with our Data Architect and report to the Engineering Pillar Lead.

Requirements

5+ years in data engineering, with at least 1–2 years in a tech lead or senior-lead capacity.
Proven experience integrating heterogeneous data sources — this is a must. You should be able to speak in depth about platforms you've built that pull together systems with very different data models, update frequencies, and access patterns.
Strong SQL and Python — you write production-quality code, not just notebooks.
Hands-on experience with a cloud data warehouse — Snowflake strongly preferred.
Experience with modern transformation tooling such as dbt.
Comfort working across cloud infrastructure (AWS preferred), not just application code.
Experience with workflow orchestration tools such as Airflow.
A track record of helping engineers grow — through mentorship, feedback, and the space to develop their own judgment.

Nice To Haves

Exposure to TypeScript or JavaScript.
Experience integrating SaaS, ERP, or HR platform APIs.
Familiarity with managed connector platforms.
Exposure to data contract or schema registry patterns.

Responsibilities

Lead the Team: Raise team standards through mentoring, code reviews, and setting a strong technical example.
Provide hands-on coaching and development for a team member based remotely, building their technical capability and confidence over time.
Act as the team's technical anchor — the person others turn to when problems get hard.
Own the Platform: Take end-to-end ownership of the data platform, from ingestion through to transformation and orchestration.
Shape engineering practice and standards as the platform and team scale.
Heterogeneous Data Integration (Core Requirement): Design integrations across a range of source systems, each with its own data model, API style, and update rhythm.
Navigate the practical realities of multi-source data — from inconsistent formats to unpredictable delivery.
Build patterns that are reusable and maintainable, not one-off solutions.