Description:

Our client is looking for a Mid-Level Data Engineer to join their growing data team.
In this role, you will independently design, build, and maintain data pipelines and infrastructure to support data-driven decision-making across the organization.
You will take ownership of key features or subsystems, help scale engineering best practices, and contribute to the mission of building a high-performance, resilient data platform.
Key responsibilities include designing and implementing medium-complexity components within the data stack, debugging, refactoring, and optimizing data systems for scalability and performance.
You will mentor junior engineers and interns to foster a culture of learning and growth.
Participation in sprint planning, technical design reviews, and cross-functional collaboration is expected.
You will also contribute to documentation, onboarding, and process improvements within the team.

Requirements:

A minimum of 2–5 years of experience in data engineering or a related software engineering role is required.
Proficiency in technologies relevant to the data stack, such as SQL, Python, Spark, Airflow, and dbt, is essential.
A solid grasp of system design, performance trade-offs, and infrastructure scalability is necessary.
A strong understanding of testing, code quality, and data validation practices is required.
Excellent communication skills and the ability to collaborate with cross-functional teams are mandatory.