Data Engineer
3d Design Tools
Automation
AWS
Aws Data Engineer
Aws Data Warehouse
Big Data
Cloud
Cloud Architecture
Cloud Data Warehouse
Cloud Data Warehouse
Cloud Infrastructure
Cloud Platform
Cloud Platforms
Cloud Technology
CloudFormation
Data
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Engineering
Data Integration
Data Lake
Data Management
Data Modeling
Data Operations
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Transforms
Data Warehouse
Data Warehousing
Database
Databases
Dbt
DevOps
DevSecOps
Ecs Fargate
ETL
Eventbridge
Informatica
Information Technology (IT)
Infrastructure As Code
Integration
Security Automation
Security Devops
Snowflake
Software Development
SQL
Sqs
Job Description
Hybrid Data Engineer role in Tampa, FL (hybrid) focused on reliable cloud data pipelines, dbt transformations, and production-grade security.
Responsibilities
- Maintain and optimize production data pipelines using AWS services such as S3, Redshift, ECS, and SFTP integrations
- Build, test, and maintain dbt models to support dependable and efficient data transformations
- Monitor pipeline performance, data accuracy, and overall system health; troubleshoot and resolve production issues
- Ensure security and compliance through system updates, dependency upgrades, vulnerability remediation, and patching
- Collaborate with engineering teams using Git, pull requests, code reviews, and CI/CD processes
- Use AI-assisted development tools including Claude and Cursor to improve development efficiency and workflow
- Create and maintain technical documentation, operational procedures, and communicate system updates across teams
- Work with the Senior Data Engineer on infrastructure improvements and scalable data solutions
Requirements
- 3–5 years of professional experience in data engineering or a related technical role
- Strong SQL skills and experience with cloud data warehouses such as Amazon Redshift, Snowflake, or BigQuery
- Proficiency in Python for pipeline development, scripting, and automation
- Hands-on experience with AWS services including S3, IAM, ECS, or Lambda
- Production experience with dbt and data transformation workflows
- Experience using Git, including pull requests and collaborative code review practices
- Knowledge of security best practices, monitoring, dependency management, and vulnerability remediation
- Familiarity with AI-assisted development tools and interest in incorporating AI into daily workflows
- Strong problem-solving, communication, and collaboration skills
Technologies
- AWS, S3, Redshift, ECS, SFTP, dbt, Git, CI/CD, Claude, Cursor
- SQL, Snowflake, BigQuery, Python, IAM, Lambda
- Docker, ECS/Fargate, Terraform, CloudFormation
- EventBridge, SQS, Dependabot, Snyk, AWS Inspector
- Amazon SageMaker, machine learning pipelines
Benefits
- Competitive salary
- Comprehensive health, dental, and vision insurance
- Direct mentorship from an experienced Senior Data Engineer
- Opportunity to take ownership of production systems and make a meaningful impact
- Hands-on exposure to modern AWS cloud infrastructure and AI-driven engineering tools
- Positive and collaborative work culture
- Paid time off
- Professional growth and development opportunities
- Employee referral bonus program
Bonus Points
- Experience with Docker, ECS/Fargate, Terraform, or CloudFormation
- Familiarity with AWS EventBridge, SQS, or other event-driven architectures
- Experience with security tools such as Dependabot, Snyk, or AWS Inspector
- Background in financial services, lending, or another regulated industry
- Exposure to machine learning pipelines or Amazon SageMaker
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