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Analytics Engineer Dbt Jobs in Florida (NOW HIRING)

Strong programming skills in Python and SQL. * Experience with modern data stack tools (e.g ... dbt, Airflow). * Proven experience building and maintaining large-scale data pipelines. * Excellent ...

Snowflake Developer

Tallahassee, FL

$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 ...

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 ...

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 ...

Senior Data Engineer

Tallahassee, FL · Remote

$100K - $136K/yr

... dbt, Python, SQL, and related technologies. As part of our growing Cloud Data & AI Platform ... Strong analytical, problem-solving, and communication skills. Additional qualifications are a plus

Senior Data Engineer

Tallahassee, FL · Remote

$100K - $136K/yr

... dbt, Python, SQL, and related technologies. As part of our growing Cloud Data & AI Platform ... Strong analytical, problem-solving, and communication skills. Additional qualifications are a plus

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 ...

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 ...

... analysts, and cross-functional teams to translate business requirements into technical solutions ... DBT Strong Python programming skills with the ability to develop scalable and maintainable ...

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 are popular job titles related to Analytics Engineer Dbt jobs in Florida?

For Analytics Engineer Dbt jobs in Florida, the most frequently searched job titles 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 78% Full Time, and 22% Contract. Highlights an 74% In-person, and 26% Remote job distribution.

Information Technology_USA - USA_Developer

Real Soft, Inc.

Jacksonville, FL • On-site

$106K - $127K/yr

Contractor

This job post has expired 3 days ago. Applications are no longer accepted.


Job description

**Please strictly adhere to the following resume naming convention:
ALL CAPS, NO SPACES BETWEEN UNDERSCORES
PTN_US_GBAMSREQID_CandidateBeelineID
Example: PTN_US_9999999_SKIPJOHNSON0413
: -
MSP Owner: Michelle Lee
Location: Marlborough, NH
Duration: 6 months
skill id: 10715995
Experience Required
5+ years of hands-on data engineering experience
3+ years focused on the Databricks / Spark ecosystem
Key Responsibilities
Data Pipeline Development
Design, develop, and deploy robust, scalable batch and streaming data pipelines using:
PySpark
Spark SQL
Delta Live Tables
Ingest data from multiple source systems, including:
Point-of-Sale (POS)
E-commerce platforms
Loyalty systems
Marketing clouds
Data Modeling & Transformation
Implement complex data transformations and business logic using the Medallion Architecture:
Bronze
Silver
Gold
Build, optimize, and maintain Gold-layer customer dimension tables as the single source of truth for Customer 360 use cases.
Data Quality & Reliability
Design and implement data quality frameworks and cleansing routines.
Ensure accuracy, consistency, and trustworthiness of Customer 360 datasets.
Performance & Cost Optimization
Proactively monitor, debug, and tune Databricks jobs and Spark clusters.
Apply best practices for:
Partitioning
Caching
Delta Lake data layout
Optimize workloads for performance and cost efficiency.
Infrastructure as Code & CI/CD
Partner with DevOps teams to manage:
Databricks environments
Clusters
Job deployments
Use Infrastructure as Code (IaC) tools such as:
Terraform
AWS DevOps
GitHub Actions
Champion CI/CD best practices for data pipelines.
Data Governance & Security
Implement governance capabilities using Databricks Unity Catalog, including:
Data lineage tracking
Role-based access controls
Data masking
Ensure compliance with organizational security and data standards.
Collaboration
Work closely with:
Functional Consultants
Data Scientists
Analytics Engineers
Translate data requirements into well-structured, consumption-ready datasets.
Required Skills & Qualifications
Databricks & Spark Expertise
Deep hands-on experience with the Databricks Lakehouse Platform, including:
Delta Lake
Structured Streaming
Delta Live Tables
Cluster configuration and optimization
Programming & Data Engineering
Expert-level proficiency in Python and PySpark.
Advanced SQL skills for transformation, validation, and analysis.
Strong understanding of ETL / ELT design patterns.
Data Warehousing Concepts
Strong knowledge of data modeling principles, including:
Dimensional modeling (Kimball)
Data warehousing fundamentals
Cloud & Software Engineering
Proven experience with a major cloud platform:
AWS, Azure, or GCP
Strong familiarity with cloud storage (e.g., S3 or equivalent).
Hands-on experience with:
Git version control
Code reviews
Testing
CI/CD pipelines
Preferred Qualifications (Nice to Have)
Databricks Certified Data Engineer - Professional certification.
Experience with Terraform or other IaC tools.
Experience delivering data solutions in retail or e-commerce environments.
Familiarity with orchestration tools such as Airflow.
Experience with modern data stack tools, including:
dbt
Snowflake
Fivetran
Experience with Customer Data Platforms (CDPs) or Master Data Management (MDM) solutions., Project Code :