Head of Analytics Engineering & Data Architecture

ConsultNet Technology Services and Solutions; New York (NY); Hybrid; USD 280,000 - 320,000; Full time

Job summary

ConsultNet Technology Services and Solutions in Midtown, New York, seeks a Director of Analytics Engineering to own data modeling and BI strategy. This hybrid role leads the data/analytics engineering team and sets the long-term direction for the data warehouse while staying hands-on for complex modeling or pipeline issues.

You will build scalable dimensional models, partner with business teams to translate needs into robust data structures, and govern data quality and standards across the

Qualifications

• 10+ years in data or analytics engineering, including leading a team.
• Comfortable moving between big-picture strategy and hands-on technical work.
• Strong, hands-on background in dimensional data modeling.
• Advanced SQL skills and experience with optimizing performance at scale.
• Experience with modern transformation tooling and a cloud-based warehouse.
• Track record of hiring, developing, and managing technical talent.

Responsibilities

• Set strategy and direction for how the company's data is warehoused, modeled, and reported on.
• Build out well-structured, reusable data models and marts that support company-wide analytics.
• Work directly with business teams to turn reporting and analysis needs into reliable data structures.
• Build, manage, and develop a team of data/analytics engineers.
• Put in place standards for data accuracy, consistency, and governance.
• Act as the connective tissue between engineering, product, and business stakeholders on data initiatives.

Skills

Dimensional data modeling

Advanced SQL

Cloud data warehouse

Team leadership

Data analytics strategy

Performance tuning

Job description

ConsultNet Technology Services and Solutions in Midtown, New York, seeks a Director of Analytics Engineering to own data modeling and BI strategy. This hybrid role leads the data/analytics engineering team and sets the long-term direction for the data warehouse while staying hands-on for complex modeling or pipeline issues.

You will build scalable dimensional models, partner with business teams to translate needs into robust data structures, and govern data quality and standards across the