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Senior Data Engineer at Worth AI. Location Information: Orlando, Florida, United States - Remote. . Worth AI, a leader in the computer software industry, is looking for a talented and experienced . Senior Data Engineer. to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.. As a . Senior Data Engineer,. you will lead the design and development of data services and platforms that power our AI-driven products. You'll focus on creating well-structured, validated APIs and event-driven . pipelines. , enabling scalable, secure, and maintainable data workflows. This is a backend-heavy role ideal for engineers who thrive on clean architecture, automation, and cross-functional delivery.. Responsibilities. . Design and build production-grade **FastAPI services** to serve, validate, and enrich data for ML and analytics use cases. . Create and maintain **asynchronous event-driven pipelines** using . . *Apache Kafka**, ensuring reliable and scalable communication across microservices. . Define and enforce structured data contracts using **Pydantic** and OpenAPI standards. . Develop robust, containerized data services with **Docker** and deploy them using modern cloud-native tooling. . Build and optimize analytical models and data flows in **Amazon Redshift** for business-critical reporting and data science consumption. . Collaborate with data scientists, ML engineers, and backend developers to streamline data sourcing, transformation, and model inference. . Own the lifecycle of data services — including monitoring, observability, testing, and deployment pipelines. . Maintain rigorous standards around data privacy, schema governance, and system performance. . Design, build, code and maintain large-scale data processing systems and architectures that support AI initiatives.. . Develop and implement data pipelines and . ETL. processes to ingest, transform, and load data from various sources.. . Design and optimize databases and data storage solutions for high performance and scalability.. . Collaborate with cross-functional teams to understand data requirements and ensure data quality and integrity.. . Implement data governance and data security measures to protect sensitive data.. . Monitor and troubleshoot data infrastructure and pipeline issues in a timely manner.. . Stay up-to-date with the latest trends and technologies in data engineering and recommend improvements to enhance the company's data capabilities.. . Requirements. . . 7+ years of professional experience in backend-focused data engineering or platform development. . Strong proficiency in **Python**, with hands-on experience using **FastAPI**, **Pydantic**, and asynchronous programming patterns. . Deep understanding of **event-driven architectures** and experience with **Kafka** (producers, consumers, schema evolution, retries, etc.). . Experience designing and deploying **containerized services** with **Docker** (Kubernetes or Fargate experience is a plus). . Proficiency in SQL and experience with modern cloud data warehouses, preferably **Amazon Redshift**. . Familiarity with cloud services (preferably AWS), including CI/CD, infrastructure-as-code, and observability tooling. . Experience integrating third-party APIs and working with versioned schema contracts. . Strong communication and collaboration skills, especially in cross-functional and agile teams. . . . Experience working with ML engineers to operationalize models (e.g., batch scoring, online inference, data validation at model boundaries). . In-depth knowledge of data modeling, data warehousing, and database design principles.. . Strong programming skills in Python, SQL, and other relevant languages.. . Experience with relational and NoSQL databases, such as PostgreSQL, MySQL, MongoDB. . Proficiency in data integration and ETL tools, such as Apache Kafka, Apache Airflow, or Informatica.. . Familiarity with big data processing frameworks, such as Hadoop, Spark, or Flink.. . Knowledge of cloud platforms, such as AWS, Azure, or GCP, and experience with data storage and processing services in the cloud.. . Understanding of data governance, data privacy, and data security best practices.. . Strong problem-solving and troubleshooting skills, with a focus on data quality and system performance.. . Excellent communication and collaboration skills to work effectively with cross-functional teams.. . Prior collaborative work with data scientists or machine learning professionals with respect to sourcing, processing and scaling both input and output data. . Comfortable going through documentation of third-party API’s and identifying best procedures for integrating data from API’s into broader ETL processes . . . Benefits. . Health Care Plan (Medical, Dental & Vision). . Retirement Plan (401k, IRA). . Life Insurance. . Unlimited Paid Time Off. . 9 paid Holidays. . Family Leave. . Work From Home. . Free Food & Snacks (Access to Industrious Co-working Membership!). . Wellness Resources. . .