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Analytics Engineer Dbt Jobs in Florida (NOW HIRING)

Build and maintain scalable data pipelines, transformations, and models that power AI workloads using Snowflake, dbt, and Airflow. * Collaborate across data, product, analytics, and engineering teams ...

Data Engineer

Miami, FL · Remote

$155K/yr

We design and build modern data platforms, analytics, and ML/AI Agent solutions for mid‑market ... Our teams work with technologies like Databricks, Snowflake, dbt, and the broader Microsoft ...

Data Engineer

Jupiter, FL · Remote

$110K - $150K/yr

Collaborate with data scientists, analysts, and business stakeholders to understand and support ... Experience with dbt for data transformation * Familiarity with real-time streaming data pipelines

Snowflake Developer (Tallahassee, FL)

Tallahassee, FL · On-site

$108K - $130K/yr

Re-engineer legacy reporting logic (e.g., WebFOCUS, Mainframe FOCUS, and T-SQL) by translating them ... g., dbt, Airflow). * Partner with analysts and business users to build efficient, reusable data ...

Snowflake Developer (Tallahassee, FL)

Tallahassee, FL · On-site

$108K - $130K/yr

Re-engineer legacy reporting logic (e.g., WebFOCUS, Mainframe FOCUS, and T-SQL) by translating them ... g., dbt, Airflow). Partner with analysts and business users to build efficient, reusable data ...

Partnering closely with product, analytics, engineering, and business stakeholders, the Senior ... Data Factory, dbt, Snowflake, Salesforce, and related platforms. • Review and guide data ...

Proficiency in SQL, DBT, and Python in a data science context; proficiency in Tableau a strong plus. * Strong command of best practices for data modeling, data transformations, and data quality ...

Knowledge of designing data warehouses and data marts that support analytics, ML, and dashboard ... DBT (Data Build Tool), or equivalent orchestration systems, with the ability to schedule, monitor ...

Showing results 41-60

Analytics Engineer Dbt information

What is an analytics engineer dbt?

An Analytics Engineer specializing in dbt (data build tool) is responsible for transforming raw data into clean, well-structured datasets that enable data-driven decision-making. They bridge the gap between data engineers and analysts by writing modular, reusable SQL code in dbt to build and maintain data models. Their role involves managing data transformations, ensuring data quality, and optimizing performance within a modern data stack.

What do analytics engineer dbt professionals do?

As an Analytics Engineer Dbt, you'll focus on designing and building robust data transformation pipelines using dbt, ensuring that raw data is modeled into well-structured, analysis-ready datasets for downstream users. Your daily responsibilities typically include collaborating with data analysts, data engineers, and business stakeholders to define data requirements, building documentation, performing code reviews, and maintaining high standards of data quality. You may also participate in optimizing query performance, automating data validation processes, and contributing to data governance initiatives. This role offers the opportunity to work at the intersection of analytics and engineering, providing both technical challenges and strategic business impact.

What are the key skills and qualifications needed to thrive as an analytics engineer dbt?

To thrive as an Analytics Engineer Dbt, you need expertise in SQL, data modeling, and modern data warehousing concepts, often supported by a degree in computer science, data analytics, or a related field. Proficiency with dbt (data build tool), version control systems like Git, and familiarity with cloud data platforms such as Snowflake, BigQuery, or Redshift is essential, with dbt certification considered a plus. Strong problem-solving abilities, communication skills, and a collaborative mindset help in effectively translating business needs into scalable data solutions. These skills are crucial for building reliable analytics workflows, ensuring data quality, and bridging the gap between data engineering and analytics teams.

What are the most commonly searched types of Analytics Engineer Dbt jobs in Florida?

The most popular types of Analytics Engineer Dbt jobs in Florida are:

What job categories do people searching Analytics Engineer Dbt jobs in Florida look for?

The top searched job categories for Analytics Engineer Dbt jobs in Florida are:

Infographic showing various Analytics Engineer Dbt job openings in Florida as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 92% In-person, and 8% Remote job distribution.

Staff Data Engineer

Material Bank

Fort Lauderdale, FL

Full-time

Re-posted 14 days ago


Job description

Material Bank is the world's largest material marketplace for the architecture and design industry. Operating in 37 countries, our platform has become the standard for design professionals around the globe. Every day, Material Bank connects thousands of designers with tens of thousands of materials from leading brands. Material Bank is the fastest and most powerful way for design professionals to search, sample, and specify materials.

We're looking for a Staff Data Engineer to lead the design, development, and operation of AI agents that power intelligent experiences across the Material Bank platform. This role sits at the intersection of data engineering, applied AI, and platform innovation, with the opportunity to shape how AI is embedded into the core of our business and customer experience. You'll be the technical lead defining how we build AI agents, with direct access to the teams interfacing with Snowflake with room to influence architecture decisions, and the chance to work across the full AI stack from data modeling and semantic layers to agent orchestration and production operations.

This is an exciting opportunity for someone who is, at their core, a passionate data engineer with deep curiosity about AI and significant experience building strong data foundations before expanding into applied AI and agent based systems. We are looking for someone who enjoys solving complex technical problems, experimenting with emerging technologies, and turning ambiguous ideas into scalable, production ready solutions. Working hands-on with Snowflake Cortex as our primary AI platform, you will help push the boundaries of what modern AI systems can do in an enterprise environment while helping define the future of intelligent experiences at Material Bank.

What You'll Do

  • Design, build, and operate production grade AI agents, owning the full lifecycle from prototyping and evaluation through deployment, monitoring, and continuous improvement.
  • Lead the development of scalable AI and data services, including MCP servers and REST APIs that expose intelligent capabilities to products, applications, and internal teams.
  • Serve as our internal expert on Snowflake Cortex, going deep on Cortex Agents, Cortex Analyst, and Cortex Search while partnering directly with Snowflake's account and product teams to influence capabilities and shape how we apply the platform.
  • Apply modern agent architecture patterns including RAG, tool use, orchestration, memory, and evaluation frameworks to build reliable, accurate, and cost efficient AI systems.
  • Partner closely with Analytics & Insights team to design and maintain semantic and metrics layers that create consistent business definitions across AI, analytics, and reporting use cases.
  • Build and maintain scalable data pipelines, transformations, and models that power AI workloads using Snowflake, dbt, and Airflow.
  • Collaborate across data, product, analytics, and engineering teams to translate ambiguous business problems into well designed AI and data solutions.
  • Establish engineering standards and best practices for agentic systems, including observability, evaluation, prompt management, governance, and operational guardrails.

What You'll bring:

  • Deep experience and genuine passion for data engineering, with strong instincts around data modeling, pipeline architecture, scalability, data quality, and building reliable platforms. Strong data foundations are core to this role.
  • 5+ years of experience in data engineering, AI/ML engineering, or related fields, including recent hands on experience building and shipping LLM powered applications or AI agents into production environments.
  • Experience building production APIs and services, including MCP servers and REST based architectures.
  • Strong understanding of modern agent development patterns including RAG, vector search, prompt engineering, tool/function calling, and frameworks such as LangChain, LangGraph, or LlamaIndex.
  • Deep expertise in Snowflake, including performance optimization, warehouse architecture, and scalable data modeling approaches such as dimensional modeling or Data Vault.
  • Production experience with dbt and Airflow, including building and maintaining semantic or metrics layers.
  • Strong Python engineering skills and solid experience working within AWS environments including services such as S3, IAM, Lambda, ECS, or similar.
  • Hands on experience using AI powered engineering tools such as Claude Code or similar development accelerators as part of real world engineering workflows.
  • Excitement about specializing deeply in Snowflake Cortex and helping define our long term AI platform strategy.

Nice to Have

  • Hands on experience working with Snowflake Cortex in production environments.
  • Experience with LLM evaluation, tracing, and observability platforms such as LangSmith, Arize, or Langfuse.
  • Experience partnering closely with analytics or BI teams to operationalize business metrics and semantic models.
  • Experience with Go, or a demonstrated ability to quickly learn and apply new technologies and programming languages.

What you'll get from us:

  • Our people: We are a growth-driven team that values efficiency, builds smart automation, operates in small empowered teams, and moves quickly from idea to execution.
  • Relaxation and Celebrations: Flexible PTO, Sick Days, Paid National Holidays, and even more (ask us about this when we connect).
  • Health Benefits: We contribute to your medical, dental, vision and short-term/long-term disability plans and have a strong employee assistance program.
  • Plan for your Retirement: 401(k) eligible after your first 90 day's employed!
  • Giving Back: We sponsor multiple events throughout the year to help out our communities.
  • Growth: We'll help you take your career to the next level. We want you to be creative and take initiative which will allow you to grow and create within the company. Most importantly, be the best at what matters!
  • Flexible Work Schedules: With business units and employees across the globe, Material Technologies has embraced a hybrid  working model allowing department leaders to decide on the best approach for their respective teams, whether that be remote, in person, or a little of both.

Material Bank is proud to be an equal opportunity employer. We value diversity, and all applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, age, national origin, veteran or disability status or other status protected under any applicable federal, state or local law.