Data Engineer - Data Warehouse & Analytics

Stack

Responsibilities

• ▹Design and implement dimensional data models: star schemas, slowly changing dimensions, serving reporting, analytics, and ML use cases
• ▹Build, optimize, and maintain robust ELT workflows feeding the data warehouse and downstream analytical layers
• ▹Refactor legacy ETL into layered, tested, documented transformation models
• ▹Own warehouse performance and cost: distribution and sort key design, workload management, materialization strategy
• ▹Establish data quality as code: automated tests, freshness checks, and contracts with upstream data producers
• ▹Document models, metric definitions, and naming conventions so analysts can self-serve
• ▹Work with Data Scientists and Analysts to translate business requirements into scalable data models
• ▹Identify technical risks in the analytical layer and drive improvements in reliability and design

Requirements

• ▹5+ years in data engineering or analytics engineering with a data warehouse at the center of your work
• ▹Expert SQL: window functions, CTE-heavy transformations, query plan analysis, and performance tuning on an MPP warehouse

About the company

Lensa.com is one of the biggest recruitment and career platforms in the United States, with 20+ million registered users. Founded by Hungarian professionals who also built Profession.hu. The Budapest team uses machine learning to match job seekers with positions.