Data Engineer

Quick Facts

• Role: Data Engineer

• Focus: Build and maintain an internal data lakehouse for analytics and AI-ready data

Description

Own the build and ongoing maintenance of an internal data lakehouse that provides data for internal analytics and data-driven decision making. Build and maintain SQL-based pipelines, integrate third-party APIs, standardize and match schemas across sources, and keep pipelines resilient through quality checks and monitoring. Optimize cost and performance, develop dashboards, and prepare clean, documented datasets for internal AI tools.

Responsibilities

• Build and maintain data pipelines in Airflow, SQL, and BigQuery feeding internal analytics tools

• Connect third-party APIs and standardize incoming data

• Match schemas across sources when blending new data into existing datasets

• Implement data quality checks, monitoring, and cataloguing

• Optimize jobs and queries to manage cost and performance

• Develop dashboards and prepare clean, documented data for internal AI tools

• Run proofs of concept on new technologies and document upgrade/switch recommendations

Requirements

• 1.5+ years of experience in a data engineering role

• Experience with managed cloud services on AWS, GCP, or Azure

• SQL experience and a modern programming language, ideally Python

• Experience with a SQL database such as BigQuery, ClickHouse, Snowflake, or Postgres, including query optimization

• Experience pulling data from third-party APIs

Nice to have

• Experience with Airflow and/or dbt

• Experience with GCP and BigQuery

• Familiarity with adtech data and metrics

• Experience preparing documented, clean data for AI tools

Benefits

• Hybrid working with flexible schedule

• 1 month work-from-anywhere

• Annual performance bonus

• Multikafeteria (sport/culture card)

• LoopMe Gives Back

• Learning and development support