Quick overview
SeniorityMid Senior
Work modeOn Site
LocationThe Woodlands, TX, United States
Stakeholder ManagementSQLGitSnowflakePythonVaultdbtAzureData AnalysisAzure Data Factory
Job description
Role: Expert Data Analytics Engineer
Duration: Longterm
Duration: Longterm
Location: Houston, TX
Onsite interview and 5 days Onsite
We are looking for a highly experienced, hands-on Expert Data Analytics Engineer with deep expertise in DBT, Snowflake, and enterprise dimensional data modeling to design, optimize, and govern the analytical foundation that supports enterprise reporting, self-service analytics, and strategic decision-making.
Key Responsibilities
* Design, develop, and lead implementation of complex star-schema data models, including fact, dimension, bridge, and aggregate tables.
* Build, optimize, and govern DBT frameworks, models, testing strategies, and reusable development patterns.
* Architect, optimize, and troubleshoot large-scale Snowflake data structures, pipelines, and SQL workloads.
* Define and enforce enterprise data modeling standards, best practices, and design patterns.
* Lead architectural decisions related to dimensional modeling, normalization, denormalization, and analytical data structures.
* Partner with Data Engineers, BI Developers, Product Owners, Architects, and business stakeholders to deliver scalable analytical solutions.
* Mentor team members, conduct design reviews, and provide technical leadership across analytics engineering initiatives.
* Drive data quality, performance, governance, documentation, and continuous improvement of the analytics platform.
* Design, develop, and lead implementation of complex star-schema data models, including fact, dimension, bridge, and aggregate tables.
* Build, optimize, and govern DBT frameworks, models, testing strategies, and reusable development patterns.
* Architect, optimize, and troubleshoot large-scale Snowflake data structures, pipelines, and SQL workloads.
* Define and enforce enterprise data modeling standards, best practices, and design patterns.
* Lead architectural decisions related to dimensional modeling, normalization, denormalization, and analytical data structures.
* Partner with Data Engineers, BI Developers, Product Owners, Architects, and business stakeholders to deliver scalable analytical solutions.
* Mentor team members, conduct design reviews, and provide technical leadership across analytics engineering initiatives.
* Drive data quality, performance, governance, documentation, and continuous improvement of the analytics platform.
Required Qualifications
* Expert-level hands-on experience with DBT development, testing, and deployment practices.
* Expert-level experience with Snowflake architecture, performance tuning, and SQL optimization.
* Proven experience designing and implementing enterprise-scale dimensional data models.
* Deep understanding of data warehousing, analytical modeling, and modern analytics engineering principles.
* Experience leading technical design decisions and influencing data architecture strategy.
* Strong communication and stakeholder management skills with the ability to translate complex technical concepts into business value.
Preferred Qualifications
* Azure Data Factory (ADF), Synapse, or Microsoft Fabric.
* Python for data engineering, automation, and analytics.
* Data Vault or advanced data modeling methodologies.
* DP-203, SnowPro, or equivalent cloud data certifications.
Ideal Candidate
A recognized technical expert who combines deep hands-on engineering expertise with architectural leadership. This individual excels at designing scalable analytical data models in DBT and Snowflake, establishing engineering standards, mentoring teams, and driving enterprise analytics capabilities while remaining actively engaged in solution delivery.
* Top 3 skill sets/technologies required for qualification:
o Strong hands-on experience with DBT development and testing, experience with Snowflake Architecture and SQL optimization.
o Enterprise Data Modeling (Dimensional Modeling)
o DevOps and Observability – GitHub, Data Dog, etc.
Onsite
Interview is in person 60-90 minutes - for next week Needs this person ASAP so no time for relocation.
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