Data Engineer

Expression

4d•Remote

About The Position

As a Data Engineer at Expression, you will help design, build, and improve the data platform that enforces quality and governance to provide timely, trustworthy analysis across enterprise systems. You will work closely with senior engineers, analysts, and stakeholders in a highly collaborative environment, contributing to well-designed data solutions while continuing to grow your technical depth and system ownership. The ideal candidate is hands-on, curious, and dependable. You are comfortable working on complex data problems, communicating clearly with teammates, and improving systems through thoughtful execution and iteration.

Requirements

4–7 years of combined experience and education in Computer Science, Information Systems, Software Engineering, Data Engineering, or a related field.
Hands-on experience building and maintaining ETL/ELT data pipelines and working with data warehouses, data lakes, or analytics platforms.
Experience working with SQL and familiarity with performance tuning and optimization concepts.
Exposure to data visualization or BI tools such as Tableau, Power BI, Superset, or similar.
Strong Python development experience
Familiarity with modern data tooling and workflows; experience using AI-assisted development tools is a plus.
Strong written and verbal communication skills, with the ability to explain technical concepts to both technical and non-technical audiences.
Ability to work effectively in a collaborative, remote-first environment.

Nice To Haves

Experience with cloud-based data solutions on AWS or Azure.
Experience working with relational and NoSQL databases such as PostgreSQL, Elasticsearch, MongoDB, or similar technologies.
Familiarity with data modeling best practices and data quality frameworks.
Experience working in agile or iterative development environments.
Interest in learning and applying generative AI tools within data engineering workflows.

Responsibilities

Build and maintain data pipelines that support ingest, logging, validation, transformation, and secure data access.
Contribute to the development and improvement of scalable ETL/ELT processes under guidance from senior engineers.
Implement and evolve data models and storage patterns that support analytics and operational use cases.
Apply data quality checks, monitoring, and documentation to ensure data is accurate, reliable, and well understood.
Collaborate with internal teams and clients to understand data requirements and support analytics use cases.
Contribute to the ongoing development of Expression’s VOR Data Platform, including tooling, standards, and automation.
Participate in research, prototypes, and proof-of-concept work to evaluate new data and analytics technologies, including emerging AI-driven tools.
Follow established engineering practices and contribute ideas to improve reliability, performance, and developer experience.