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Principal Data Engineer Jobs in Florida (NOW HIRING)

Sidram Technologies

Data Scientist

Juno Beach, FL · On-site

Onsite - 5 Days / Week - Juno Beach Florida JD:- Principal Data Scientist - Load & Renewable ... Advanced feature engineering, uncertainty quantification, and probabilistic forecasting methods

SAIC

Big Data Engineer Principal

Orlando, FL · On-site

$106K - $128K/yr

Big Data Engineer Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance Required: Secret Clearance Level Must Be Able to Obtain: None Potential for Remote Work: ORA_ON ...

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All JobsPrincipal Data Engineer JobsPrincipal Data Engineer Jobs in Florida

Principal Data Engineer information

See Florida salary details

$55.3K

$110K

$158.8K

How much do principal data engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for principal data engineer in Florida is $110,016.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,600.00 and $129,300.00 per year, depending on experience, location, and employer.

What engineers make 500,000?

Principal Data Engineers and senior engineering roles in fields like software, cloud, and machine learning can reach salaries of $500,000 or more, especially with extensive experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant funding.

What are the typical daily responsibilities of a Principal Data Engineer?

As a Principal Data Engineer, your day-to-day responsibilities generally include designing and optimizing large-scale data pipelines, developing architectural strategies, and overseeing the implementation of robust data solutions. You'll collaborate closely with data scientists, analysts, and software engineers to ensure the organization's data infrastructure is efficient, scalable, and secure. You may also mentor junior team members, review code, and set data engineering best practices. This role frequently requires balancing hands-on technical work with strategic planning and stakeholder communication to align data initiatives with business goals.

What is a Principal Data Engineer job?

A Principal Data Engineer is a senior-level technical role responsible for designing, building, and maintaining large-scale data infrastructure. They lead data engineering teams, establish best practices, and ensure efficient data pipelines to support analytics and machine learning. This role involves working with cloud platforms, big data technologies, and distributed systems to optimize data processing. Principal Data Engineers collaborate with data scientists, analysts, and business stakeholders to drive data-driven decision-making. Their work is critical in enabling organizations to leverage data effectively for insights and innovation.

What engineers make $300,000 a year?

Principal Data Engineers and senior engineering roles in fields like software, machine learning, and cloud infrastructure can earn $300,000 or more annually, especially with extensive experience, advanced skills, and certifications. Compensation often includes base salary, bonuses, and stock options, particularly in high-demand industries or large tech companies.

What does a principal data engineer do?

A principal data engineer designs, develops, and maintains large-scale data systems and pipelines to support data analysis and business decision-making. They often lead data architecture initiatives, collaborate with data scientists and engineers, and ensure data quality, security, and compliance using tools like SQL, Spark, and cloud platforms. This role typically requires extensive experience in data engineering, strong problem-solving skills, and leadership abilities.

How much do principal data engineers make?

Principal data engineers typically earn between $120,000 and $180,000 annually, with salaries varying based on experience, location, and industry. They often have advanced skills in data architecture, cloud platforms, and programming languages like Python or Scala, and may receive bonuses or stock options depending on the company.

What are the key skills and qualifications needed to thrive in the Principal Data Engineer position, and why are they important?

To thrive as a Principal Data Engineer, you need a deep understanding of data architecture, data modeling, ETL development, and distributed computing, often supported by a degree in computer science or a related field. Proficiency with technologies such as Hadoop, Spark, Python, SQL, and cloud platforms (AWS, Azure, or Google Cloud), as well as certifications in relevant tools or data engineering, is highly valuable. Strong leadership, problem-solving skills, and effective cross-functional communication are essential soft skills for this role. These combined abilities enable Principal Data Engineers to design scalable data solutions, drive engineering best practices, and lead complex projects to successful completion.

What are the most commonly searched types of Principal Data Engineer jobs in Florida? The most popular types of Principal Data Engineer jobs in Florida are:
What are popular job titles related to Principal Data Engineer jobs in Florida? For Principal Data Engineer jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Principal Data Engineer jobs in Florida look for? The top searched job categories for Principal Data Engineer jobs in Florida are:
Principal Data Engineer jobs near you
Infographic showing various Principal Data Engineer job openings in Florida as of June 2026, with employment types broken down into 54% Full Time, and 46% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $110,016 per year, or $52.9 per hour.

Principal Data Architect

Raymond James Financial, Inc.

Saint Petersburg, FL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Job description

Job Description Summary
The Principal Data Architect is a senior enterprise architecture and strategy leader within the Enterprise Data & Analytics Architecture team. This role defines and advances the enterprise data architecture vision, target-state patterns, data platform strategy, and adoption roadmap across on-premises and cloud environments. The Principal Data Architect partners with senior technology leaders, data engineering teams, enterprise data management, analytics consumers, security, risk, compliance, and business stakeholders to deliver scalable, secure, reusable, and business-aligned data capabilities.
Job Description
This position follows our hybrid-friendly schedule, so you get the best of both worlds - flexibility and collaboration. In office days will be 2-3 per week averaging 10-12 days per month in our St Petersburg, FL Corporate Office.
Responsibilities
  • Data Lakehouse and Warehouse Architecture: Own reference architectures and design patterns for enterprise data Lakehouse and warehouse platforms, including AWS Redshift, Apache Iceberg, Oracle Exadata, S3, Glue, Lake Formation, Athena, EMR, Presto, Airflow, and related ecosystem capabilities.
  • Data Modeling and Design Leadership: Lead the design of logical, conceptual, and physical data models using ER Studio or similar tools. Establish modeling standards across normalized, dimensional, Data Vault, star, snowflake, and denormalized approaches. Resolve complex modeling issues that span multiple systems and business domains.
  • Architecture Standards and Reuse: Create and maintain data architecture principles, design standards, reusable patterns, architecture decision records, reference implementations, and best-practice guidance that can be adopted across programs.
  • Data Access and Consumption Strategy: Define enterprise data access patterns, consumption models, and fit-for-purpose tool guidance for BI, advanced analytics, operational reporting, AI/ML, data products, APIs, and self-service use cases. Recommend appropriate access controls, semantic layers, and data sharing mechanisms.
  • Platform and Technology Strategy: Evaluate, rationalize, and guide selection of data tools, storage formats, integration technologies, metadata platforms, quality tooling, lineage capabilities, and cloud-native services. Balance innovation, cost, complexity, security, vendor risk, and operational maturity.
  • Real-Time and Batch Data Architecture: Define patterns for both batch and real-time data movement, including Kafka schemas, event-driven design, data contracts, schema governance, replication, CDC, ETL/ELT, medallion architecture layers, and data quality controls across pipelines.
  • Thought Leadership and Innovation: Monitor emerging trends in cloud data platforms, lakehouse architectures, data mesh, data products, AI-ready data, metadata automation, data observability, and financial services data architecture. Recommend pragmatic adoption paths that strengthen enterprise capabilities.
  • Governance, Metadata, Lineage, and Data Quality: Partner with Enterprise Data Management and governance teams to embed metadata, lineage, data quality, cataloging, ownership, privacy classification, retention, and stewardship expectations into platform and solution architecture.

Skills
  • Must have deep, hands-on experience in wealth management, asset management, brokerage, private client services, or closely related financial services domains.
  • Proven ability to influence senior stakeholders, guide complex architectural decisions, mentor architects or senior engineers, and lead through ambiguity.
  • Expert level knowledge of Data Architecture, Data Modeling, Data Lake house and data warehouse design methodologies (star schema, snowflake schema, normalization, denormalization).
  • Proficient with database technologies: Oracle (including RAC, Exadata), SQL Server, AWS Redshift, and replication tools like Oracle Golden Gate and AWS DMS.
  • Advanced SQL, PL/SQL development, and database performance tuning skills.
  • Deep expertise in AWS Data Ecosystem-Athena, Iceberg, Lake Formation, Glue, EMR, Sagemaker, S3, Airflow, Aurora, Presto.
  • Skilled in scripting and automation (Shell, Python).
  • Data integration architecture: Ability to architect ETL/ELT, streaming, event-driven, API-based, file-based, and replication-based data flows, including data contracts, schema evolution, lineage, quality checks, and operational monitoring.
  • Data Lakehouse & Data Marketplace Architecture: Proven experience designing and operationalizing enterprise-scale data lake, Lakehouse, or data marketplace platforms, including governed data onboarding, metadata management, data product publishing.
  • AI Data Readiness & Semantic Data Enablement: Demonstrated ability to assess, structure, and curate enterprise data for AI, advanced analytics, and GenAI use cases, including defining semantic models, ontologies, knowledge graphs.

Education/Previous Experience:
  • Bachelor's degree in Computer Science, MIS, or related field.
  • 10+ years of progressive experience in data architecture, data engineering, database architecture, enterprise architecture, or large-scale data platform delivery.

Licenses/Certifications:
  • AWS or relevant cloud certification highly preferred.

Education
Bachelor's: Computer and Information Science (Required), Bachelor's: Computer Engineering
Work Experience
General Experience - 10 to 15 years
Certifications
Travel
Less than 25%
Workstyle
Hybrid
The total compensation for this position includes base salary or wages, and may include components such as additional compensation (cash or equity), discretionary bonuses, or commissions. This position is eligible for a benefits package that may include medical, dental, and vision; life insurance; critical illness insurance and accident insurance; disability benefits; retirement savings; paid time off (including vacation, holidays, and sick leave); and parental leave. Eligibility for benefits and specific offerings may vary based on position and employment status. To view more details of the benefits offered, visit Myrjbenefits.com.
At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
• Grow professionally and inspire others to do the same
• Work with and through others to achieve desired outcomes
• Make prompt, pragmatic choices and act with the client in mind
• Take ownership and hold themselves and others accountable for delivering results that matter
• Contribute to the continuous evolution of the firm
At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.
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