Technology Lead Data Modeler (Database / Databricks)@

Job Title: Technology Lead – Data Modeler (Database / Databricks)

Location: Houston, TX 77077 (Onsite – relocation accepted)

Contract Duration: 6 Months

Start Date: October 22, 2025

Experience Required: 10+ Years

Visa: Only Visa-Independent Candidates

POC: Sam Chavez

Job Summary:

We are seeking a Technology Lead – Data Modeler to join our client’s data engineering team in Houston, TX. The ideal candidate will have extensive experience in data modeling, database design, and data architecture, with a strong working knowledge of Databricks and Python/PySpark. This role involves leading the design and implementation of enterprise-grade data models that enable scalable analytics and reporting solutions.

Key Responsibilities:

Lead data modeling efforts across enterprise data initiatives, ensuring alignment with business and technical requirements.

Design, develop, and maintain logical and physical data models to support analytics, reporting, and data integration.

Work with cross-functional teams—including data architects, analysts, and business stakeholders—to translate business needs into optimal data structures.

Ensure data quality, governance, and consistency across multiple systems and environments.

Provide guidance and mentorship to junior team members in data modeling best practices.

Collaborate with engineering teams to implement and optimize models in Databricks and cloud environments.

Support data transformation and integration activities using Python/PySpark and related tools.

Must-Have Skills:

Data Modeling (conceptual, logical, and physical)

Databricks awareness

Strong database design and implementation experience

Python / PySpark proficiency

Nice-to-Have Skills:

Leadership and team mentoring

Strong accountability and communication skills

Interview Process:

Mode: Virtual / Face-to-Face as required

Mandatory Submission Details:

Updated phone number, email, and Skype ID

Five (5) interview time slots within 72 hours of profile submission

Incomplete submissions will be automatically rejected