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Senior Data Engineer Jobs in Florida (NOW HIRING)

Senior Data Engineer

Tallahassee, FL · Remote

$95K - $129K/yr

Data Engineering Reports to: Senior Director of Data Platform Engineer Location: Remote Responsibilities * Design and Implement Snowflake-Native Data Architectures * Lead the creation and ...

Senior Data Engineer

Orlando, FL · On-site

$98K - $134K/yr

Intellisoft Technologies is working with Disney Streaming, a leading premium streaming service, to find a Senior Data Engineer. The successful candidate will build foundational datasets from ...

Senior Data Engineer

Orlando, FL · On-site

$98K - $134K/yr

Intellisoft Technologies is seeking a Senior Data Engineer for Disney Streaming, a leading premium streaming service. The role involves building foundational datasets from clickstream and quality of ...

Senior Data Engineer

Miami, FL · On-site

$101K - $137K/yr

We are looking for a Senior Data Engineer to join our growing data platform team. You will own the design, build, and reliability of our cloud-native data lakehouse -- from raw ingestion through to ...

Senior Data Engineer

Miami, FL · On-site

$149K - $170K/yr

Rumble is seeking a Senior Data Engineer to design, build, and operate the data platforms and backend systems that support large-scale product, analytics, and operational workloads. This is a senior ...

As a Senior Data Engineer in Research IT, you will play a critical role supporting Bristol Myers Squibb's Foundational Data Products , including CoreReg, Substance Mart, DARE, and Asset Mart . You ...

Senior Data Engineer

Miami, FL · On-site

$149K - $170K/yr

Rumble is seeking a Senior Data Engineer to design, build, and operate the data platforms and backend systems that support large-scale product, analytics, and operational workloads. This is a senior ...

Rumble is seeking a Senior Data Engineer to design, build, and operate the data platforms and backend systems that support large-scale product, analytics, and operational workloads. This is a senior ...

Senior Data Engineer

Tampa, FL · On-site

$99K - $225K/yr

R0245470 Data Engineer, Senior The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence means that there's more structured and unstructured data available ...

Sr. Data Engineer

Saint Petersburg, FL · Remote

$100K - $136K/yr

As a Senior Data Engineer, you will be a key technical contributor and operational owner within our data engineering function. You will bring deep Snowflake expertise and strong engineering instincts ...

Senior Data Engineer

Miami, FL · Hybrid

$10K - $12K/mo

The ideal candidate is a US-based Senior Data Engineer who can step into an established enterprise data warehouse environment as a hands-on contributor and a peer-level thought partner to the client ...

Senior Data Engineer

Tampa, FL · On-site

$77K - $176K/yr

R0245463 Data Engineer, Senior The Opportunity: Ever-expanding technology like IoT, machine learning, and artificial intelligence means that there's more structured and unstructured data available ...

Overview As a Senior Data Engineer, you will play a pivotal role in driving our data strategy and standard methodologies for data collection, pipelines, usage, and infrastructure. We are looking for ...

Showing results 21-40

Senior Data Engineer information

See Florida salary details

$60.5K

$94.4K

$130.8K

How much do senior data engineer jobs pay per year?

As of Aug 8, 2026, the average yearly pay for senior data engineer in Florida is $94,404.00, according to ZipRecruiter salary data. Most workers in this role earn between $79,200.00 and $107,600.00 per year, depending on experience, location, and employer.

What is a senior data engineer?

Senior Data Engineers are experienced professionals who design, build, and maintain large-scale data processing systems and infrastructure. They are responsible for developing data pipelines, managing databases, and ensuring the efficient flow and integrity of data across various platforms. Senior Data Engineers often collaborate with data scientists, analysts, and other engineers to support business intelligence and machine learning projects. They also play a key role in implementing best practices for data security, quality, and governance within an organization.

What is the difference between Senior Data Engineer vs Data Scientist?

AspectSenior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with data pipelinesBachelor's/Master's in CS, Statistics, or related; proficiency in statistical analysis and modeling
Work EnvironmentBuild and maintain data infrastructure, optimize data workflowsAnalyze data, develop predictive models, generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data engineering is essentialResearch, marketing, tech firms focusing on data analysis and modeling

While both roles work with data, Senior Data Engineers focus on developing and maintaining data infrastructure, whereas Data Scientists analyze data to generate insights and build models. They often collaborate but have distinct skill sets and responsibilities.

What are some common challenges senior data engineers face when integrating data from multiple sources?

Senior Data Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues requires designing robust ETL (Extract, Transform, Load) pipelines, implementing data validation checks, and collaborating closely with source system owners to ensure data integrity. Effective communication with cross-functional teams and leveraging scalable data integration tools are also essential to streamline the process and minimize errors.

How much do senior data engineers get paid?

Senior data engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and industry. They often possess skills in SQL, Python, cloud platforms, and data pipeline tools, which can influence compensation levels.

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

To thrive as a Senior Data Engineer, you need strong expertise in data modeling, ETL development, programming (such as Python or Scala), and a degree in computer science or a related field. Proficiency with big data technologies (like Hadoop, Spark), cloud platforms (AWS, Azure, GCP), and database systems, as well as relevant certifications, is highly valuable. Excellent problem-solving, communication, and leadership skills help you collaborate across teams and mentor junior engineers. These skills and qualities ensure robust, scalable data solutions that support organizational decision-making and growth.
What are the most commonly searched types of Data Engineer jobs in Florida? The most popular types of Data Engineer jobs in Florida are:
What job categories do people searching Senior Data Engineer jobs in Florida look for? The top searched job categories for Senior Data Engineer jobs in Florida are:
What cities in Florida are hiring for Senior Data Engineer jobs? Cities in Florida with the most Senior Data Engineer job openings:
What are popular job titles related to Senior Data Engineer jobs in FL? For Senior Data Engineer jobs in FL, the most frequently searched job titles are:
Infographic showing various Senior Data Engineer job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $94,404 per year, or $45.4 per hour.

Senior Data Engineer

Trulieve

Tallahassee, FL • Remote

$95K - $129K/yr

Other

PTO

Re-posted 28 days ago


Trulieve rating

5.3

Company rating: 5.3 out of 10

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Job description

If you have an interest in being part of one of the fastest growing industries in the nation in you may consider wanting to work for Trulieve! If you have a desire to help others in need through your efforts, this may be the role for you! 

At Trulieve, we strive to bring our patients the relief they need in a product they can trust. Our plants are hand-grown in an environment specially designed to reduce unwanted chemicals and pests, keeping the process as natural as possible at every turn.

Our products are designed to alleviate seizures, severe and persistent muscle spasms, pain, nausea, loss of appetite, and other symptoms associated with serious medical conditions such as cancer.

Our specially trained staff works hand-in-hand with physicians to provide the right products and the correct dosage to ensure patients get the compassionate care they need.

To learn more about our company, please visit our website; 

https://www.trulieve.com

Requisition ID:  19863 

Remote Work Available: Yes 

Job Title: Senior Data Engineer 
Department: Data Engineering
Reports to: Senior Director of Data Platform Engineer

Location: Remote

Responsibilities
  • Design and Implement Snowflake-Native Data Architectures
    • Lead the creation and optimization of modern data architectures on Snowflake, including multi-layer pipelines (bronze/silver/gold), real-time streaming ingestion, and governed analytics layers.
    • Ensure that the architecture supports high-volume data workloads, near-real-time freshness requirements, and integrates seamlessly with upstream operational systems and downstream analytics consumers.
  • Lead the Development of Complex, End-to-End Data Pipelines Using Native Snowflake Services
    • Architect and build data pipelines using Dynamic Tables for declarative SQL-based transformations with automated dependency management and incremental refresh.
    • Implement real-time and near-real-time ingestion using Snowpipe and Snowpipe Streaming.
    • Design event-driven and procedural pipeline logic using Streams and Tasks for complex orchestration scenarios (MERGE, SCD patterns, external function calls).
    • Leverage Snowpark (Python) for advanced transformations that require procedural logic beyond SQL.
  • Collaborate with Data Scientists, Analysts, and Other Stakeholders
    • Work closely with analytics and data science teams to understand data requirements and translate them into scalable, performant Snowflake solutions.
    • Build and maintain Semantic Views and governed consumption layers that provide self-service access to curated data.
    • Provide technical guidance on Snowflake best practices for data usage, cost optimization, and warehouse sizing.
  • Ensure Data Security, Governance, and Compliance Standards Are Met
    • Implement and manage Snowflake data governance features including Dynamic Data Masking, Row Access Policies, Object Tagging, and Data Classification.
    • Establish and maintain data governance frameworks ensuring data quality and compliance with relevant regulations (SOX, GDPR, HIPAA).
    • Manage role-based access control (RBAC), data sharing, and cross-account governance using Snowflake's native security model.
Skills
  • Deep Understanding of Data Engineering Concepts
    • Extensive knowledge of data modeling, including designing and maintaining relational, dimensional, and semi-structured data models within Snowflake.
    • Proficiency in data warehousing concepts with hands-on experience designing multi-layer transformation pipelines (staging, intermediate, marts).
    • Strong understanding of incremental processing patterns, change data capture (CDC), and slowly changing dimension (SCD) strategies.
  • Expertise in Snowflake Platform and Native Data Pipeline Services
    • Deep proficiency with Snowflake Dynamic Tables (TARGET_LAG, REFRESH_MODE, pipeline dependency graphs, incremental vs. full refresh).
    • Hands-on experience with Snowpipe and Snowpipe Streaming for continuous and real-time data ingestion.
    • Strong knowledge of Snowflake Streams and Tasks for event-driven and procedural pipeline orchestration.
    • Experience with Snowpark (Python/Scala) for complex data transformations and UDFs/UDTFs.
    • Familiarity with Snowflake Cortex AI functions for embedding AI/ML capabilities into data pipelines.
  • Proficiency in SQL, Python, and Data Engineering Frameworks
    • Advanced SQL skills including window functions, CTEs, recursive queries, semi-structured data handling (VARIANT, OBJECT, ARRAY), and performance optimization.
    • Python proficiency for Snowpark development, automation scripting, and integration work.
    • Experience with modular SQL transformation development, testing, and documentation using native Snowflake patterns and shared engineering standards.
    • Familiarity with orchestration platforms such as Apache Airflow / Astronomer for pipeline scheduling and monitoring.
  • Experience with Real-Time Data Processing and Streaming Architectures
    • Hands-on experience designing solutions for real-time and near-real-time data pipelines using Snowpipe Streaming and Kafka connectors.
    • Understanding of event-driven architectures and their integration with Snowflake's continuous data pipeline features.
    • Experience with change data capture (CDC) patterns and tools (Debezium, Fivetran, custom CDC).
  • Strong Knowledge of Cloud Infrastructure and Cost Optimization
    • Expertise in cloud platforms (AWS, Azure, or GCP) with a focus on integration with Snowflake (external stages, storage integrations, PrivateLink).
    • Experience with Snowflake cost management including warehouse sizing strategies, auto-suspend/resume, resource monitors, and query optimization.
    • Familiarity with infrastructure-as-code tools (Terraform, Pulumi) for managing Snowflake resources declaratively.
Contributions
  • Lead the Technical Design of New Projects
    • Responsible for making critical decisions regarding Snowflake architecture patterns, product direction, and delivery tradeoffs, including when to use Dynamic Tables, Streams/Tasks, Materialized Views, and external orchestration based on business requirements and user needs.
    • Develop and enforce best practices for pipeline development, testing, deployment, and monitoring within the team.
    • Design and document data contracts and SLAs for pipeline freshness (TARGET_LAG), data quality, and availability.
  • Mentor and Develop Junior Engineers
    • Provide technical leadership and mentorship to junior and mid-level engineers, fostering a culture of continuous learning and improvement.
    • Lead code reviews, pair programming sessions, and technical workshops focused on Snowflake-native development patterns and engineering best practices.
    • Create reusable patterns, templates, and documentation for common pipeline scenarios (CDC ingestion, SCD management, real-time aggregations).
  • Operate as a Product Minded Data Engineering Leader
    • Partner with business stakeholders, analytics teams, and engineering leaders to shape the roadmap for data products and platform capabilities based on business value, user needs, and operational priorities.
    • Translate ambiguous business problems into clearly defined product requirements, success metrics, delivery plans, and prioritized engineering work.
    • Own the lifecycle of key data products and shared platform services, including intake, prioritization, stakeholder alignment, adoption, and continuous improvement.
  • Continuously Evaluate and Improve Existing Systems
    • Regularly review current data systems to identify opportunities for migration to modern patterns (for example, migrating legacy Streams/Tasks to Dynamic Tables where appropriate).
    • Monitor pipeline health, refresh performance, and cost efficiency using Snowflake's INFORMATION_SCHEMA, ACCOUNT_USAGE, and alerting capabilities.
    • Implement optimizations including incremental refresh tuning, warehouse right-sizing, and query performance improvements.
Experience
  • Substantial Professional Experience in Data Engineering
    • Typically requires 7+ years of experience in data engineering or related fields.
    • Proven track record of designing and implementing large-scale data solutions on Snowflake or similar cloud data platforms.
    • 2+ years of hands-on experience with Snowflake-native pipeline services (Dynamic Tables, Streams/Tasks, Snowpipe).
Training & Certifications
  • Snowflake and Cloud Data Engineering Certifications
    • Preferred certifications include SnowPro Advanced: Data Engineer, SnowPro Core, or AWS/Azure/GCP data engineering certifications.
    • Continuous learning through relevant certifications and training to stay current with Snowflake platform releases and modern data engineering practices.
    • Familiarity with Snowflake's release cycle and ability to evaluate new features (for example, Cortex AI, Document AI, Iceberg Tables) for team adoption.

Salary will be commensurate with experience.   A comprehensive benefits package including paid time off is offered with this position. 

Trulieve provides equal employment opportunities to all employees and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, pregnancy or any other characteristic protected by federal, state or local laws.


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