Data Engineer

Worth AI

Orlando, FL

Vision , Medical , Dental , Paid Time Off , Life Insurance , Retirement
Full-Time

Worth AI, a dynamic player in the computer software industry, is seeking a skilled and motivated individual to join their team as a Data Engineer. Worth AI is committed to transforming decision-making using the power of AI while promoting equity, diversity, and inclusion. With core values centered around diversity of thought, teamwork, and adaptability, Worth AI is dedicated to making a positive impact in the business world.

As a Data Engineer at Worth AI, you will play a crucial role in designing and implementing data pipelines, data integration solutions, and data infrastructure to support the company's AI initiatives. You will collaborate closely with data scientists, software engineers, and other stakeholders to ensure effective data management and accessibility. Your expertise in data processing, data modeling, and database optimization will be essential in delivering scalable and reliable data solutions.

Responsibilities

Design, build, 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

Proven experience as a Data Engineer or similar role, preferably in a software or technology-driven company with experience processing several to several hundreds of Gigabytes of data or more
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