JOBSEARCHER
SIGN IN

Senior Data Engineer

ARCHIVED

We can't find an active application page for this role right now. It may reopen or be listed elsewhere. Use Next Steps to search for an active apply link and similar live jobs.

Position Summary: We are seeking a Senior Data Engineer to join a collaborative engineering team focused on building scalable, high-performance data solutions. In this role, you will design, develop, and optimize modern data pipelines and data platforms that transform complex data into actionable insights. You'll work closely with cross-functional teams to deliver reliable, efficient, and scalable data solutions that support business-critical initiatives.What the right candidate will enjoy:Working in a fast-paced and highly collaborative environment.Engaging with customers to understand and prioritize innovative new offerings and incremental technology improvements.Being part of a team that values agile methodologies and continuous improvement.Job Must Haves:5+ years of data engineering experienceStrong understanding of data modeling principlesProficiency in at least one major programming language (e.g., Python)Expert SQL skillsHands-on production experience with data pipeline orchestration systems such as AirflowExperience with SnowflakeStrong algorithmic problem-solving expertiseExcellent written and verbal communicationBachelor’s degree in computer science, Information Systems, or equivalent industry experienceFamiliar with Scrum and Agile methodologiesAdvance understanding of OLTP vs OLAP environmentsWillingness and ability to learn and pick up new skill setsSelf-starting problem solver with an eye for detailWhat the responsibilities are of the right candidate:Create and maintain Data Platform pipelines.Design table structures using DBT and define data pipelines to build performant, reliable, and scalable data solutions.Collaborate with other data engineers, data scientists, and cross-functional teams (product managers, architects, etc.Document standards and best practices for pipeline configurations, naming conventions, etc.Ensure high operational efficiency and quality of the Core Data Platform datasets.