Data Engineer New York, NY $130,000 – $165,000

NvLynx Analytics LLC; New York (NY); Hybrid; USD 55,000 - 96,000; Part time

Job summary

NvLynx Analytics LLC seeks a remote, project-based business analyst / technical writer for US-based engagements. You will run definition workshops, draft KPI dictionaries, and document data models and product definitions for client teams, including higher-ed stakeholders.

Responsibilities include facilitating sessions, delivering clear technical writing, and ensuring privacy and accuracy of dean-level data while aligning with project timelines.

Qualifications

• Experience running definition workshops and writing KPI dictionaries.
• Ability to document data definitions for non-technical audiences.
• Experience with higher-ed reporting (IPEDS, state, accreditation) is a plus.

Responsibilities

• Run definition workshops and capture requirements.
• Write KPI dictionaries and governance artifacts.
• Document what is built and explain data models to stakeholders.

Skills

Definition workshops

KPI dictionaries

Technical writing

Facilitation

Clear communication

Higher-ed reporting

Job description

We deliver larger engagements with a small, vetted bench of independent contractors. Work is remote, project-based, and led by our principal architect.

Roles we work with

• SQL Server or Oracle
• dbt
• Python
• Airflow or Dagster
• Banner or another SIS/ERP (preferred)

Builds semantic models and leadership dashboards from approved definitions.

• SSAS Tabular or Power BI semantic models
• DAX
• Tabular Editor

Business analyst / technical writer

Runs definition workshops, writes KPI dictionaries, and documents what we build.

• Higher-ed reporting (IPEDS, state, accreditation)
• Facilitation
• Clear technical writing

How engagements work

• Remote, U.S.-based, with occasional client meetings by video
• Part-time and flexible; most assignments run a few weeks to a few months
• A master services agreement and NDA before any client work
• Victor leads every engagement and reviews all work before it reaches the client

What we look for

Purpose before platform You care what the work is for, not only which tool it uses.

Engineering discipline Version control, tests, and documentation are part of the job, not extras.

Plain language You can explain a data model to a dean and a definition to an engineer.

Discretion Student and staff data, and client names, stay private. Always.