Analytics Engineering Lead — AI-Driven Data Platform

Unifocus; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Unifocus seeks an Analytics Engineering Manager to lead analytics and BI engineering, driving evolution toward a scalable, data-platform‑driven ecosystem. You will stay hands-on while mentoring a small team and guiding architectural direction.

The role emphasizes AI‑enabled analytics, data modeling, and delivering reliable analytics capabilities. The position combines leadership with technical execution, preparing assets for AI‑driven use cases and ensuring governance, performance, and

Qualifications

• 8+ years in BI/analytics engineering or data engineering
• 2+ years leading technical teams and delivery
• Hands-on SQL expertise with transformations and modeling
• Experience with enterprise BI platforms (QuickSight, Power BI, Tableau, Cognos)
• Knowledge of modern data warehousing and cloud data platforms
• Strong understanding of dimensional and analytical modeling
• Ability to balance technical execution with leadership

Responsibilities

• Lead design, development, and maintenance of analytics solutions and dashboards.
• Set engineering standards, optimize performance, and ensure data quality.
• Modernize BI landscape and align with data platform strategy.
• Mentor a small BI/analytics team and manage delivery priorities.
• Collaborate with product, data engineering, and AI stakeholders.

Skills

SQL

Data modeling

Leadership

Analytics engineering

Cloud data platforms

Tools

Amazon QuickSight

Power BI

Tableau

Cognos

Dundas

Logi SaaS BI tools

Job description

Unifocus seeks an Analytics Engineering Manager to lead analytics and BI engineering, driving evolution toward a scalable, data-platform‑driven ecosystem. You will stay hands-on while mentoring a small team and guiding architectural direction.

The role emphasizes AI‑enabled analytics, data modeling, and delivering reliable analytics capabilities. The position combines leadership with technical execution, preparing assets for AI‑driven use cases and ensuring governance, performance, and