Senior Data Engineer

Worth AIOrlando, FL, US

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Job Description

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

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Senior Data Engineer • Orlando, FL, US