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Contract Dbt Sql Jobs (NOW HIRING)

Radix

Data Engineer

Scottsdale, AZ

$115K - $138K/yr

Build and maintain robust dbt models, testing frameworks, documentation, schema contracts, and ... Deep expertise with Databricks (or similar modern data platforms), dbt, SQL, Python, and scalable ...

Centstone

Data Engineer

Sunnyvale, CA · On-site

$75 - $85/hr

... onsite contract opportunity with a leading technology client in Sunnyvale, California. The ideal candidate will have strong expertise in Snowflake, SQL, ETL, DBT, Tableau, Python, and Data ...

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How much do contract dbt sql jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for contract dbt sql in the United States is $52.60, according to ZipRecruiter salary data. Most workers in this role earn between $43.51 and $59.62 per hour, depending on experience, location, and employer.

What is a contract dbt sql professional?

Contract DBT SQL professionals are data specialists hired on a contractual basis to design, build, and maintain data transformation workflows using DBT (Data Build Tool) and SQL. They help organizations organize, clean, and transform raw data into reliable datasets for analytics and business intelligence purposes. Their responsibilities often include developing data models, writing complex SQL queries, implementing testing protocols, and ensuring data quality. These experts are typically engaged for specific projects or to fill temporary skill gaps within data teams. Contract DBT SQL professionals must have strong SQL skills, familiarity with data warehousing concepts, and hands-on experience with DBT.

What are some common challenges faced by contract dbt sql professionals when joining a new project?

Contract DBT SQL professionals often encounter challenges such as quickly understanding the existing data infrastructure, adapting to varied coding standards, and integrating with established teams. Since contract roles usually require fast onboarding, you may need to familiarize yourself with unfamiliar data sources and business logic on a tight timeline. Effective communication and proactive documentation are key to navigating these transitions and ensuring your work aligns with project goals.

What are the key skills and qualifications needed to thrive as a contract dbt sql developer, and why are they important?

To thrive as a Contract DBT SQL Developer, you need strong SQL expertise, experience with data modeling, and proficiency in dbt (data build tool), often supported by a background in computer science or data engineering. Familiarity with cloud data warehouses (such as Snowflake, BigQuery, or Redshift), version control systems like Git, and dbt Cloud or CLI usage is typically required. Excellent problem-solving abilities, attention to detail, and effective communication skills help you understand business requirements and deliver accurate data solutions. These skills ensure reliable data pipelines, maintainable analytics workflows, and successful collaboration within data-driven teams.

What is the difference between Contract Dbt Sql vs Data Analyst?

AspectContract Dbt SqlData Analyst
Required SkillsSQL, dbt, data modeling, ETL processesSQL, data visualization, reporting, data interpretation
Work EnvironmentProject-based, remote or on-site, technical teamsBusiness units, cross-functional teams, often office-based
CertificationsSQL certifications, dbt certifications beneficialData analysis certifications (e.g., Microsoft, Tableau)

Contract Dbt Sql professionals focus on building data pipelines and transformations using dbt and SQL, often in technical environments. Data Analysts interpret data, create reports, and support business decisions. While both roles require SQL skills, Contract Dbt Sql roles are more technical and development-oriented, whereas Data Analysts focus on analysis and visualization.

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Contract Dbt Sql jobs near you
Infographic showing various Contract Dbt Sql job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 89% Full Time, 2% Part Time, and 8% Contract. Highlights an 78% Physical, 6% Hybrid, and 16% Remote job distribution, with an average salary of $109,407 per year, or $52.6 per hour.

Data Engineer

Radix

Scottsdale, AZ

$115K - $138K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted yesterday

Key responsibilities

  • Design, build, and maintain scalable ETL/ELT pipelines that ingest data from files, databases, APIs, and third-party systems into trusted, analytics-ready data products.

  • Own the reliability, performance, governance, and cost optimization of Radix's Databricks-based data platform, including orchestration, data quality, observability, and root cause analysis.

  • Build and maintain robust dbt models, testing frameworks, documentation, schema contracts, and semantic-layer assets that create trusted, scalable data products.

Job description

About Radix
Radix is revolutionizing how the multifamily world makes decisions. From investment to divestment, and everything in between, Radix brings data transparency, market intelligence, and acquisition modeling into a seamless ecosystem that turns the industry's best insights into confident decisions.

What You Will Be Part Of

We’re looking for a highly capable, hands-on Data Engineer to help build the foundation for Radix’s next generation of data and AI products.

This is a strong individual contributor role for someone who wants to solve hard data problems, build reliable systems, and raise the bar for how data moves, models, and powers decision-making across the business. You will work closely with the Head of Data Engineering and cross-functional partners across Product, Engineering, Analytics, and AI Systems to improve the quality, reliability, and usability of Radix’s data platform.

You’ll be stepping into an environment with multi-product system complexity, a real legacy estate that we are actively retiring rather than living with, an in-flight migration between clouds, and real stakes. The right person will be able to diagnose where trust breaks down, improve pipeline reliability, strengthen data modeling practices, and build production-grade systems that support both analytics and AI-enabled product experiences.

Beyond traditional data engineering, this role will help shape the semantic layer that powers Radix’s AI products. That means designing data systems with LLM consumption in mind: clean metric definitions, reliable context surfaces, governed access patterns, and data infrastructure that agents can actually trust.

What You Will Achieve 

  • Design, build, and maintain scalable ETL/ELT pipelines that ingest data from files, databases, APIs, and third-party systems into trusted, analytics-ready data products.

  • Own the reliability, performance, governance, and cost optimization of Radix's Databricks-based data platform, including orchestration, data quality, observability, and root cause analysis.

  • Build and maintain robust dbt models, testing frameworks, documentation, schema contracts, and semantic-layer assets that create trusted, scalable data products.

  • Define and enforce data contracts, metric definitions, and modeling standards that support consistent use across analytics, product, and AI applications.

  • Partner across teams to design reliable, governed data interfaces and ensure downstream consumers can confidently use and trust the data they depend on.

  • Help build the semantic layer and AI data infrastructure that powers conversational analytics, LLM-driven experiences, and agentic workflows.

  • Design and maintain metadata, business definitions, evaluation frameworks, and governance guardrails that improve the trustworthiness of AI-generated insights.

  • Build and maintain infrastructure-as-code, CI/CD pipelines, automated testing, and deployment practices that enable reliable and scalable data platform operations.

  • Improve developer experience through better tooling, local development workflows, testing practices, environment consistency, and deployment confidence.

  • Implement production-grade monitoring, lineage, anomaly detection, alerting, and operational processes that proactively identify and resolve data issues.

  • Create documentation, runbooks, and operational playbooks that improve platform supportability, knowledge sharing, and long-term scalability.

  • Operate as a highly collaborative technical leader who aligns stakeholders, documents decisions, and helps drive a reliable, scalable, and AI-ready data ecosystem.

What Makes You a Strong Fit 

  • 5+ years of experience in Data Engineering, Analytics Engineering, or a related field, with hands-on responsibility for production data platforms and pipelines.

  • Deep expertise with Databricks (or similar modern data platforms), dbt, SQL, Python, and scalable data modeling, including governance, testing, documentation, and semantic layers.

  • Experience building and maintaining reliable data pipelines from relational databases, document stores, and object storage using modern table formats such as Delta Lake, Iceberg, and Parquet.

  • Strong understanding of cloud-based data infrastructure, including AWS, Terraform, CI/CD, orchestration platforms (Dagster, Airflow, or similar), observability, monitoring, lineage, and data quality frameworks.

  • Comfortable working in hybrid-cloud environments and making sound decisions around architecture, performance, cost optimization, reliability, and operational readiness.

  • Able to trace and resolve data issues end-to-end, implement effective data contracts, and identify risks or anti-patterns in modeling, pipeline design, and system operations before they become problems.

  • Comfortable navigating ambiguity, simplifying complex systems, and improving data quality and engineering practices without slowing delivery.

  • Actively leverage AI tools and understand how modern development practices, automation, and agentic workflows can improve engineering productivity while maintaining trust, accuracy, and governance.

  • Familiar with designing data platforms that support analytics, applications, and AI use cases through clean ontologies, predictable schemas, semantic layers, and trustworthy metrics.

  • Hands-on builder who leads through technical credibility, strong communication, collaboration, and sound judgment rather than authority.

  • High ownership mindset with a track record of delivering meaningful improvements in fast-moving, evolving environments.

  • Excited by the opportunity to build reliable, understandable, and scalable data systems that create measurable value for humans, applications, and AI agents.

Why You Will Love Working Here

  • Comprehensive Benefits

    • Medical, dental and vision coverage designed to support your wellbeing.

  • Uncapped Paid Time Off

    • We trust you to take the time you need to recharge and do your best work.

  • Pre-IPO Equity

    • Meaningful ownership with the potential to grow right alongside Radix.

  • Performance Bonus

    • Rewarded for the impact you drive, not just tasks completed.

  • Learn From the Best

    • Work shoulder-to-shoulder with industry experts, innovative operators, and leaders shaping the future of multifamily.

  • Build Category-Defining Products

    • Join us during a high-velocity, post–Series A growth stage where your ideas influence the market, not just the roadmap.

Radix does not accept unsolicited resumes or candidate submissions from staffing or recruiting agencies. We do not engage external agencies for hiring and will not be responsible for any fees associated with unsolicited submissions.