Analytics & Data Engineering (Lead or Head)

About this kind of role

What a Analytics & Data Engineering (Lead or Head) usually does. The employer's own details are in the listing.

Typically does: Leads a team responsible for building and maintaining data pipelines, transforming raw data into usable formats, and ensuring data quality. This role involves designing and implementing data warehousing solutions, developing ETL processes, and collaborating with data scientists and business analysts. A key focus is on optimizing data infrastructure for performance and scalability, and establishing data governance best practices. They often define the technical roadmap for data engineering initiatives within the organization.

Tools and skills: Proficiency in SQL, Python or similar scripting languages, experience with cloud platforms (like AWS, Azure, or Google Cloud), and familiarity with data warehousing technologies (such as Snowflake, Redshift, or BigQuery) are generally required, alongside strong leadership and communication skills.

Good fit for: Individuals with a strong technical background in data engineering and a proven ability to lead and mentor teams thrive in this role.