Lead Analytics Engineer, Data Products & ROI

Greenhouse Software; New York (NY); On-site; USD 130,000 - 150,000; Full time

Benefits offered by this job

Equity

Performance bonuses

Benefits package

Job summary

Datavations is a New York-based data and AI software leader seeking a Forward Deployed Analytics Engineer to manage client relationships and drive product development from data aggregation to delivery.

You will lead a team of data scientists and analysts, scale data products, and collaborate across data science, engineering, and sales to deliver ROI-driven insights. This role emphasizes self-starting leadership and rigorous documentation.

Qualifications

• Strong SQL and data warehousing expertise with hands-on experience.
• Proven dbt experience and dimensional data modeling.
• Experience leading 2+ developers and coordinating data-science/engineering teams.
• Familiarity with BI tools like Tableau, Power BI, Retool.
• Experience with retail or consumer data and analytics.
• Proactive documentation and self-starter mentality.

Responsibilities

• Manage client relationships and provide technical support.
• Develop and scale data pipelines from ingestion to product delivery.
• Lead a team of data scientists and data analysts to deliver innovations.
• Collaborate with data science, engineering, and sales teams.
• Drive ROI through new product lines like pricing, ecommerce intelligence, and supply chain analysis.
• Document coding efforts rigorously and train new hires.

Skills

SQL & Data Warehousing

Time-series analysis

Leadership (2+ developers)

End-to-end Data Products

Data Visualization UX

Retail / E-commerce analytics

Cross-functional collaboration

Tools

Snowflake

Google BigQuery

ClickHouse

dbt

Jira

Tableau

Power BI

Retool

Terraform

Job description

Datavations is a New York-based data and AI software leader seeking a Forward Deployed Analytics Engineer to manage client relationships and drive product development from data aggregation to delivery.

You will lead a team of data scientists and analysts, scale data products, and collaborate across data science, engineering, and sales to deliver ROI-driven insights. This role emphasizes self-starting leadership and rigorous documentation.