Data Engineer

Hybrid Position – Tampa, Florida

Symple Lending is an innovative fintech company at the forefront of transforming the lending industry by empowering customers on their journey to financial freedom. Our commitment lies in providing seamless and efficient lending solutions to our customers.

We are seeking a talented and motivated Data Engineer to join our growing team! In this role, you'll work directly with our Senior Data Engineer to maintain and enhance the cloud infrastructure and data pipelines that power our business. You'll gain hands-on experience with modern AWS technologies, take ownership of production systems, and help build scalable data solutions in a fast-paced, technology-driven environment.

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  Maintain and optimize production data pipelines using AWS technologies, including S3, Redshift, ECS, and SFTP integrations.

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  Build, test, and maintain dbt models to ensure reliable and efficient data transformations.

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  Monitor pipeline performance, data accuracy, and system health while troubleshooting and resolving issues.

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  Maintain security and compliance through system updates, dependency upgrades, vulnerability remediation, and patching.

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  Collaborate with engineering teams using Git, pull requests, code reviews, and CI/CD processes.

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  Leverage AI-assisted development tools such as Claude and Cursor to improve efficiency and streamline engineering workflows.

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  Develop technical documentation, maintain operational procedures, and communicate system updates across teams.

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  Partner with the Senior Data Engineer on infrastructure improvements and scalable data solutions.

• 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 an interest in incorporating AI into daily workflows.

• Strong problem-solving, communication, and collaboration skills.

• 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.