Data Engineer

Symple Lending is hiring a hybrid Data Engineer in Tampa, Florida to maintain and enhance cloud infrastructure and production data pipelines. The role focuses on reliable data transformations with dbt, operational monitoring, and secure deployments, working closely with engineering teams and partnering with a Senior Data Engineer on scalable solutions.

Key Responsibilities

• Maintain and optimize production data pipelines using AWS services including 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, and troubleshoot issues to restore reliability.
• Support 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 workflows.
• Use AI-assisted development tools such as Claude and Cursor to improve engineering efficiency and streamline workflows.
• Develop technical documentation, maintain operational procedures, and communicate system updates across teams.
• Partner with the Senior Data Engineer on infrastructure improvements and scalable data solutions.

Required Qualifications

• 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 data pipelines, 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, pull requests, and collaborative code-review practices.
• Knowledge of security best practices, system monitoring, dependency management, and vulnerability remediation.
• Familiarity with AI-assisted development tools and interest in using AI within daily workflows.
• Strong problem-solving, communication, and collaboration skills.

Technologies and Tools

Working knowledge may include: 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, and 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