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Dbt Data Engineer Jobs in Spring, TX (NOW HIRING)

Deloitte

Senior Forward Deployed Engineer- AWS

Houston, TX

$99K - $137K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Deloitte

Lead Forward Deployed Engineer - AWS

Houston, TX

$97K - $128K/yr

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

SmartIPlace

Azure DataLake Engineer [remote]

Houston, TX · On-site

$52.50 - $65.25/hr

Azure Datalake Engineer Desired Start Date: 2/9 Duration: 12 months or longer Workplace: Remote ... hands-on of DBT tool · Excellent communication skills · Ability to conduct data profiling ...

Deloitte

Forward Deployed Engineer- AWS

Houston, TX

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

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All JobsDbt Data Engineer JobsDbt Data Engineer Jobs in Spring, TX

Dbt Data Engineer information

See Spring, TX salary details

$39.6K

$115.4K

$158K

How much do dbt data engineer jobs pay per year?

As of Aug 15, 2026, the average yearly pay for dbt data engineer in Spring, TX is $115,433.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,900.00 and $122,400.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a dbt data engineer, and why are they important?

To thrive as a Dbt Data Engineer, you need strong SQL skills, experience in data modeling, and a solid understanding of ELT/ETL pipelines, often supported by a degree in computer science or a related field. Familiarity with dbt (data build tool), version control systems like Git, and cloud data platforms such as Snowflake or BigQuery is typically required. Attention to detail, problem-solving abilities, and effective collaboration are essential soft skills for this role. These skills ensure robust, scalable, and maintainable data transformations that drive reliable analytics and business insights.

How does a dbt data engineer typically collaborate with data analysts and other stakeholders?

As a Dbt Data Engineer, you'll work closely with data analysts, business intelligence teams, and sometimes product managers to translate business requirements into reliable, well-structured data models. Collaboration often involves reviewing transformation logic, ensuring data quality, and providing documentation or training on Dbt models. You may also participate in regular stand-ups or data modeling sessions to align on priorities and address data challenges collaboratively. Effective communication skills are key, as you'll bridge the gap between raw data and actionable insights.

What is a dbt data engineer?

Dbt Data Engineers are professionals who specialize in using dbt (data build tool) to transform, test, and document data within modern data warehouses. They build and maintain data pipelines by writing SQL-based transformation scripts and ensuring data quality through automated testing. Dbt Data Engineers collaborate closely with analytics teams to create reliable, well-documented datasets that support business intelligence and analytics initiatives.

What is the difference between Dbt Data Engineer vs Data Analyst?

AspectDbt Data EngineerData Analyst
Primary FocusBuilding and maintaining data transformation pipelines using dbtAnalyzing data to generate reports and insights
Skills & ToolsSQL, dbt, ETL pipelines, cloud platformsSQL, Excel, BI tools, data visualization
Work EnvironmentData engineering teams, cloud data platformsBusiness units, reporting teams
CertificationsSQL, cloud certifications, dbt trainingData analysis, visualization certifications

While both roles work with data and SQL, Dbt Data Engineers focus on developing scalable data transformation pipelines using dbt, whereas Data Analysts primarily analyze data to produce reports and insights. The roles complement each other within data teams but differ in technical scope and responsibilities.

What are popular job titles related to Dbt Data Engineer jobs in Spring, TX?

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What job categories do people searching Dbt Data Engineer jobs in Spring, TX look for?

The top searched job categories for Dbt Data Engineer jobs in Spring, TX are:

What cities near Spring, TX are hiring for Dbt Data Engineer jobs?

Cities near Spring, TX with the most Dbt Data Engineer job openings:

Dbt Data Engineer jobs near you

Senior Cloud Data Platform Engineer

HRC Global Services

Houston, TX • On-site

$101K - $137K/yr

Full-time

Re-posted 19 days ago

Job description

Confidential Opening – Senior Cloud Data Platform Engineer
Location: Houstan,Texas
 

Position Overview

A leading enterprise organization is seeking a highly skilled Cloud Data Platform Engineer to support the development and modernization of enterprise-scale data ecosystems. This role will focus on building trusted, scalable, and governed data solutions leveraging Snowflake, AWS, open table technologies, and semantic data modeling practices.

The ideal candidate combines strong hands-on engineering expertise with a deep understanding of data governance, metadata strategy, and business-aligned data architecture.

Core Responsibilities

  • Develop and maintain scalable data pipelines supporting structured, semi-structured, and unstructured data assets.

  • Design and optimize cloud-native data architectures utilizing Snowflake as the enterprise strategic data platform.

  • Build and support ingestion and extract-load workflows using enterprise integration technologies.

  • Create modular transformation frameworks and reusable data models using modern analytics engineering methodologies.

  • Work within AWS cloud environments to support enterprise data applications and integrated data services.

  • Support implementation of open table architectures including schema evolution, interoperability, and governed access patterns.

  • Contribute to enterprise metadata management, lineage, cataloging, policy enforcement, and governed data-sharing initiatives.

  • Partner with architects, governance teams, analysts, and business stakeholders to develop trusted and reusable data products.

  • Translate business terminology, domain concepts, and operational relationships into scalable logical and physical data models.

  • Support semantic and ontology-driven modeling initiatives including taxonomies, entity relationships, business glossaries, and semantic mapping frameworks.

  • Implement enterprise standards for data quality, observability, governance, security, and performance optimization.

  • Support AI-ready and analytics-driven use cases across enterprise applications and business intelligence platforms.

Required Qualifications

  • Strong experience in enterprise data engineering, cloud data platforms, ETL/ELT development, and data modeling.

  • Hands-on expertise with Snowflake including:

    • Warehouse/lakehouse architectures

    • Data modeling

    • Performance tuning

    • Security and access management

    • Enterprise-scale implementation patterns

  • Experience working within AWS cloud ecosystems and modern cloud-native architectures.

  • Experience with enterprise ingestion and integration tools such as Informatica or similar platforms.

  • Strong experience with dbt for transformation development, testing, documentation, and deployment workflows.

  • Understanding of Apache Iceberg or similar open table frameworks including schema evolution and managed table concepts.

  • Knowledge of metadata management, governance frameworks, data lineage, cataloging, and policy-based data access.

  • Familiarity with ontology concepts, semantic modeling, taxonomies, business glossaries, or knowledge graph frameworks.

  • Advanced SQL skills and experience with Python or related programming languages.

  • Strong stakeholder communication and documentation capabilities.

Preferred Qualifications

  • Experience with enterprise metadata and governance capabilities within Snowflake environments.

  • Experience building governed data products supporting analytics, AI, or operational applications.

  • Exposure to semantic technologies such as RDF, OWL, SHACL, SPARQL, or graph-oriented platforms.

  • Experience with CI/CD pipelines, Git-based workflows, automated testing, and deployment practices.

  • Familiarity with data observability, lineage monitoring, data contracts, and enterprise quality frameworks.

  • Prior experience working in large-scale, multi-domain enterprise data environments.