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Weekend Data Engineering Jobs in Florida (NOW HIRING)

WELLDYNE

Lead Data Engineer

Lakeland, FL · On-site

$106K - $127K/yr

Data Platform Engineering: * Design and build scalable, reliable data pipelines that ingest, transform, and load data from operational systems, clinical platforms, claims, and third-party sources.

WellDyne

Lead Data Engineer

Lakeland, FL

$106K - $127K/yr

Data Platform Engineering: * Design and build scalable, reliable data pipelines that ingest, transform, and load data from operational systems, clinical platforms, claims, and third-party sources.

Slide Insurance

Data Engineer

Tampa, FL · On-site

$108K - $129K/yr

You'll partner with engineering and business teams to deliver reliable data for reporting, analytics, and operational decision-making. What You'll Do Build Data Pipelines * Build and maintain ETL/ELT ...

KaashTech LLC

Data Engineer

Tampa, FL

$104K - $125K/yr

The ideal candidate will have 7-10 years of experience in data engineering, with a proven track record of designing and implementing data solutions that drive business insights. This role requires a ...

Andromeda Systems Incorporated

Data Engineer

Jacksonville, FL · On-site

$106K - $127K/yr

... software engineering teams to clean, migrate, and replicate data into and within SQL Server ... or weekend work may be required to support critical deliverables • Must be a U.S. Citizen • ...

Dlapiper

Data Engineer

Miami, FL · On-site

$109K - $131K/yr

In current initiatives, data engineering includes consolidating data from multiple sources into a central SQL-based integration point and performing field mapping and transformations, so solution ...

Slide Insurance

Data Engineer

Tampa, FL · On-site

$108K - $129K/yr

You'll partner with engineering and business teams to deliver reliable data for reporting, analytics, and operational decision-making. What You'll Do Build Data Pipelines * Build and maintain ETL/ELT ...

Pediatric Associates

Sr Data Engineer

Plantation, FL · On-site

$109K - $131K/yr

EXPERIENCE: • 10+ years of experience in data engineering or a related field required. • Expert-level proficiency in SQL and experience with data transformation tools (e.g., Azure Data Factory ...

Pediatric Associates

Sr Data Engineer

Plantation, FL · Remote

$109K - $131K/yr

EXPERIENCE: • 10+ years of experience in data engineering or a related field required. • Expert-level proficiency in SQL and experience with data transformation tools (e.g., Azure Data Factory ...

SmartIPlace

Data Engineer [Hybrid] w2 role

Orlando, FL · On-site

$106K - $128K/yr

Requirements * 7+ years of data engineering experience across multiple environments (e.g., Dev, QA, Production) with DevOps practices for code deployment . * Experience working with a range of ...

Cross Catholic Outreach

Data Engineer

Pompano Beach, FL · On-site

$76K - $85K/yr

Educational or Certification Requirements: · Bachelor's Degree in Information Technology, Computer Science, Data Engineering, or a related field · Microsoft Azure/Fabric or data engineering ...

Stellar IT Group

Data Engineer

Orlando, FL · On-site

$106K - $128K/yr

Strong proficiency in SQL and data engineering fundamentals. * Hands-on experience with Snowflake (tables, queries, optimization). * Expertise in Azure Data Factory (ADF) - pipeline creation ...

PROFESSIONAL STAFFING SERVICES GROUP INC

Be Seen First

Data Engineer

Orlando, FL · On-site

$90K - $110K/yr

Design, implement, test, deploy, and maintain stable, secure, and scalable data engineering solutions and pipelines, including integrating new sources into our central data warehouse and moving data ...

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Weekend Data Engineering information

What engineers make $500,000?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires specialized certifications, leadership roles, and a strong track record of managing complex data infrastructure.

Will AI replace ETL?

AI can automate parts of the ETL (Extract, Transform, Load) process, improving efficiency and reducing manual effort for data engineers. However, human oversight is still essential for designing, monitoring, and troubleshooting complex data workflows, so AI is more of a complement than a complete replacement for ETL roles.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. Skills in cloud platforms, programming languages like Python and SQL, and tools such as Apache Spark and Hadoop enhance employability in this field.

What is the difference between Weekend Data Engineering vs Weekend Data Analysis?

AspectWeekend Data EngineeringWeekend Data Analysis
Required SkillsData pipeline development, SQL, Python, cloud platformsData interpretation, visualization, SQL, Excel
Work EnvironmentTechnical teams, data infrastructure projectsBusiness teams, reporting and insights
CertificationsData engineering certifications (e.g., Google Cloud, AWS)Data analysis certifications (e.g., Microsoft, Tableau)

Weekend Data Engineering focuses on building and maintaining data pipelines and infrastructure, requiring technical skills and cloud platform knowledge. In contrast, Weekend Data Analysis emphasizes interpreting data, creating reports, and providing insights, often using visualization tools. Both roles are essential in data-driven organizations but serve different functions during weekend projects or part-time work.

What jobs make $1,000,000 a year?

High-level executive roles such as CEOs, CFOs, and other C-suite positions can earn over $1 million annually, often including bonuses and stock options. Certain specialized professions like top-tier investment bankers, hedge fund managers, and successful entrepreneurs also reach this income level, typically requiring extensive experience, advanced skills, and significant responsibility.
What are the most commonly searched types of Data Engineering jobs in Florida? The most popular types of Data Engineering jobs in Florida are:
Weekend Data Engineering jobs near you
Lead Data Engineer

Lead Data Engineer

WELLDYNE

Lakeland, FL • On-site

$106K - $127K/yr

Full-time

Posted 29 days ago

WellDyne rating

6.0

Company rating: 6.0 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

Job description

Summary
The Lead Data Engineer will design, build, and maintain the organization's enterprise data platform, leading the technical implementation of data pipelines, warehouses, and analytics infrastructure that powers business intelligence, reporting, and advanced analytics across the PBM and Pharmacy organization. This hands-on technical leadership role sets data engineering standards, mentors team members, and partners with business and technology stakeholders to deliver trusted, well-governed, and timely data products.
  • Essential Duties and Responsibilities
  • Data Platform Engineering:
  • Design and build scalable, reliable data pipelines that ingest, transform, and load data from operational systems, clinical platforms, claims, and third-party sources.
  • Develop and maintain the enterprise data warehouse, data lake, and analytical data models that serve reporting and analytics use cases.
  • Design data services and event-driven integration patterns that enable scalable downstream consumption by analytics platforms, operational systems, APIs, and AI-enabled applications.

Technical Leadership:
  • Serve as the senior technical authority for data engineering, setting standards for code quality, pipeline design, data modeling, and testing across the team.
  • Lead technical planning for data engineering initiatives, breaking work into well-scoped tasks and coordinating delivery across team members.
  • Mentorship and Collaboration:
  • Provide technical direction and code review for data engineers, ensuring consistency, quality, and adherence to standards.
  • Participate in hiring and onboarding of data engineering team members, including technical interviews and skills assessments.
  • Mentor data engineers across all levels, fostering a culture of technical excellence, knowledge sharing, and continuous improvement.

Data Architecture and Modeling:
  • Partner with the Architecture team to define and implement data architecture, including data warehouse models, data lake structures, and integration patterns.
  • Apply dimensional modeling, normalization, and modern data modeling techniques (e.g., Kimball, Data Vault) to support analytics and reporting requirements.

Performance and Reliability:
  • Optimize query performance, storage costs, and pipeline runtime across the data platform.
  • Implement observability, monitoring, and alerting for production data pipelines, and partner with operations to ensure timely incident response.
  • Identify reliability, data quality, and performance risks and develop mitigation strategies to ensure platform stability and data trustworthiness.

Data Governance and Compliance:
  • Implement controls to ensure compliance with HIPAA, PHI/PII handling, and other regulatory requirements applicable to the healthcare and pharmacy sectors.
  • Partner with security and compliance teams on access control, encryption, audit logging, and data lineage for sensitive data assets.
  • Design and enable scalable, governed data access patterns that support AI/ML systems, intelligent automation, and emerging agentic workflows, including structured, semantic, and real-time data consumption patterns.

Business Partnership:
  • Partner with analytics, business intelligence, and product teams to understand data needs and deliver fit-for-purpose datasets, models, and pipelines.
  • Translate business and reporting requirements into well-designed technical data engineering solutions.

Tooling and Innovation:
  • Evaluate and recommend new data engineering tools, frameworks, and cloud services that improve productivity, scalability, or cost-efficiency.
  • Stay current on advances in cloud data platforms, lakehouse architectures, streaming technologies, and AI/ML data infrastructure.

Support and Troubleshooting:
  • Provide production support for critical data pipelines, participating in on-call rotations as needed.
  • Diagnose and resolve complex data quality, performance, and integration issues spanning multiple systems and platforms.

Operational Oversight:
  • Implement data quality validation, backup and recovery, and pipeline monitoring to ensure continuous data delivery.
  • Recommend tooling and infrastructure needed to support the enterprise data platform.
  • Prepare and review data platform health metrics, pipeline performance reports, and project status updates.

Documentation:
  • Implement and maintain metadata, lineage, cataloging, and semantic data definitions that improve discoverability, trust, and machine usability of enterprise data assets.

Education and Experience
  • Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field or relevant experience. Master's degree in a relevant discipline preferred.
  • 8+ years of professional data engineering experience, with at least 2 years in a senior or technical lead capacity preferred.
  • Hands-on experience designing and operating enterprise data platforms in a healthcare, pharmaceutical, or Pharmacy Benefit Management environment preferred.
  • Prior experience implementing real-time data streaming pipelines that power reporting, dashboards, and operational visibility preferred.

Knowledge, Skills, and Abilities
  • Expert-level proficiency in SQL, Python, and modern data engineering frameworks (e.g., Spark, dbt, Airflow).
  • Deep experience with cloud data platforms (Snowflake, Databricks, Redshift, or BigQuery) and storage layers (S3, ADLS).
  • Strong understanding of data modeling, warehousing patterns (Kimball, Data Vault), and lakehouse architectures.
  • Strong understanding of regulatory standards affecting the healthcare and pharmacy sectors, including HIPAA.
  • Proficient in modern cloud platforms (AWS, Azure), CI/CD for data, and infrastructure-as-code tools (Terraform, CloudFormation).
  • Experience building data foundations for AI agents and RAG-based applications, including semantic modeling, metadata enrichment, vector-search integration, governed APIs/tools, and secure access patterns for machine-consumable enterprise data.
  • Familiarity with Microsoft Power BI, including semantic models, datasets, and enablement of self-service reporting and dashboards.
  • Familiarity with real-time and streaming data technologies (e.g., Kafka, Kinesis, Spark Streaming, Flink) supporting reporting and operational visibility.
  • Excellent communication skills, capable of explaining technical concepts to both engineering and business stakeholders.
  • Ability to lead technical initiatives end-to-end while mentoring engineers and driving quality and reliability.

Work Environment / Physical Demands
This position is in a typical office environment which requires prolonged sitting in front of a computer. Requires hand-eye coordination and manual dexterity sufficient to operate standard office equipment including operation of standard computer and phone equipment. May have occasional high stress when dealing with customers/clients. Some travel may be required.
EOE M/F/D/V

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