Top 1 Aws data engineer Jobs in Winter Haven, Fl

Lead Data Engineer
WellDyne —Lakeland, FL
- On call
- Computer science
- Computer Science
- HIPAA
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Lead Data Engineer
WellDyne —Lakeland, FL
The Lead Data Engineer will design, build, and maintain the organization’s enterprise data platform, leading the technical implementation of data pipelines,…
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Lead Data Engineer - Solutioning
Disney Experiences —Orlando, FL
Familiar with SQL, Python, cloud data platforms (AWS, Azure, or GCP), and modern data stack tools such as Snowflake, Databricks, Spark, Airflow, or dbt, with a…
$148,300 - $198,800 a year
10h

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Data Engineer
Proteam Solutions —Dublin, OH
We are seeking an experienced Senior Data Engineer with deep expertise in Databricks to design, develop, and optimize enterprise-scale data pipelines.
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Data Engineer (AWS, Azure, GCP)
CapTech Consulting —Columbus, OH
Experience in the design and implementation of data architecture solutions. Learning & Development – Programs offering certification and tuition support,…
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Lead Data Engineer

WellDyne -
Lakeland, FL

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Job Details

Qualifications

Performance monitoring
Data integrity assurance
Data model design
Commercial use (data warehousing systems)
Computer science
Cloud analytics services
Databricks
Data visualization software proficiency
Data Integration (Data management)
Computer Science
Engineering development testing
Project management experience in technology
Data validation techniques
IT operations
Tooling
Technical documentation
Infrastructure as Code (IaC)
AI integration
Improving system uptime or availability
Database backup and recovery
IT quality control
Spark
Regulatory compliance
Operations coordination planning
Business intelligence report generation
HIPAA
Data recovery
Information Systems
Metrics Reporting
Scalable systems

Full 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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aws data engineer jobs in winter haven, fl

Lead Data Engineer

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