Data Engineer, Senior

Eigen Development•Las Vegas, NV

About The Position

Shift4 is seeking a Senior Data Engineer to design, develop, and maintain robust data infrastructure that supports the organization’s data-driven initiatives. The role requires ownership of projects and close collaboration with project managers, business analysts, software engineers, and other cross-functional partners to ensure data systems are available, reliable, and scalable. Deep expertise in data engineering and ETL processes is required. The Senior Data Engineer develops automated pipelines to ingest, transform, and load large volumes of data from diverse sources into relational databases. The role also supports data quality, security, governance, system performance, data modeling, integration, documentation, and continuous improvement. The position participates in an Agile SDLC and may provide off-hours support when necessary.

Requirements

Bachelor's or master's degree in Computer Science, Information Systems, or a related field.
At least 2 years of experience in data engineering or a similar role.
Advanced experience with relational databases such as MSSQL, PostgreSQL, or AWS Redshift.
Advanced experience with SQL and MSSQL SSIS or other ETL tools.
Familiarity with data warehousing concepts and technologies.
Experience working in an Agile SDLC environment.
Strong problem-solving and analytical skills, with attention to detail.
Ability to prioritize multiple tasks and adjust to changing priorities.
Excellent interpersonal, verbal, and written communication skills, especially for technical documentation.
Ability to identify problems, initiate solutions, and collaborate effectively with team members.

Nice To Haves

Relevant certifications in data engineering.

Responsibilities

Design, develop, and maintain automated data pipelines and ETL processes for ingesting, transforming, and loading large volumes of data from diverse sources into relational databases.
Ensure data workflows are scalable and reliable for high-volume and complex processing.
Implement data validation, cleansing, and governance processes to protect data integrity.
Enforce data security and privacy principles throughout pipelines in accordance with regulations and best practices.
Optimize data systems for performance, scalability, and reliability.
Troubleshoot and resolve data pipeline, processing job, and database performance issues.
Provide off-hours support when necessary to maintain data system reliability.
Participate in the Agile SDLC and collaborate with cross-functional teams to deliver enhancements and resolve bugs in a timely manner.
Align development work with sprint goals and deliverables defined by Project Managers.
Aid in designing and implementing data models and schemas for analysis, reporting, and visualization.
Work with software engineers to integrate data engineering solutions into applications and software products.
Document data engineering processes, data models, and system configurations.
Stay current with emerging data engineering technologies, tools, and practices, and recommend infrastructure improvements.