Senior Data Engineer (Onsite)

First American•Miami, FL

1d•Onsite

About The Position

The Senior Data Engineer is a data expert who helps develop and deploy innovative big data platforms for advanced analytics and data processing. The role supports scalable solutions using modern technology to grow and leverage the company’s data assets. Working with functional teams, software developers, database architects, data analysts, and data scientists, the Senior Data Engineer helps ensure consistent, effective data-delivery architecture across ongoing initiatives. The position drives innovation, contributes to highly visible initiatives, and may require work outside normal hours based on business needs.

Requirements

Bachelor’s degree in Computer Science or a related field, or an equivalent combination of education and experience.
5–8 years of directly related experience.
Experience working in an Agile SDLC methodology.
Proficiency with SQL and T-SQL programming.
Working experience building data/ETL pipelines and data warehouses.
Expertise in data modeling, database maintenance, monitoring, and performance tuning on SQL Server, MongoDB, or other NoSQL databases.
Exceptional analytical skills, including analyzing large and complex data sets.
Ability to perform thorough testing and data validation to ensure the accuracy of data transformations.
Strong written and verbal communication skills, with precise documentation.
Self-driven team player able to work independently and multitask.
Analytical, creative thinker and innovative problem solver.
Working knowledge of or proficiency in modern cloud computing technology.

Responsibilities

Identify, design, and implement internal process improvements, including automating manual processes, optimizing data delivery, and redesigning infrastructure for scalability.
Design, develop, code, test, and document architectures and applications.
Work with team members and cross-functional teams to ensure designs, architecture, and deliverables meet business requirements and align with best practices.
Troubleshoot and resolve a wide range of data issues.
Recommend improvements to data reliability, efficiency, and quality.
Support the development and deployment of big data platforms for analytics and data processing.
Help ensure optimal data-delivery architecture across ongoing projects.