TL;DR

Data Engineer: Building and maintaining data pipelines for Bauer Media Audio's data business across multiple European markets with an accent on ETL/ELT processes, CUBE architecture implementation, and support of critical business initiatives. Focus on Snowflake ingestion and transformation pipelines, supporting BI and analytics use cases, and implementing data quality checks.

Location: Hybrid role based in London.

Company

%hirify_global% is a media business focused on creating content that matters to millions of people across Europe.

What you will do

Build and maintain data pipelines moving data from source systems into S3 and curated layers using Python and Airflow.
Deliver new ingestion and transformation pipelines for Snowflake while supporting Redshift and BigQuery workloads.
Develop and maintain dbt models and tests to support BI and analytics use cases.
Implement and enhance data quality checks and monitoring in Airflow.
Collaborate with senior engineers on ingestion patterns and migration approaches.
Engage with business stakeholders to ensure pipelines enable meaningful analytics.

Requirements

Strong Python and SQL skills.
Experience with Airflow for workflow orchestration.
Proven track record delivering end-to-end data pipelines in a cloud environment.
Hands-on experience with dbt and AWS.
Familiarity with Git-based workflows and CI/CD practices.
Experience implementing data quality checks and monitoring.
2+ years in data/analytics engineering roles.

Nice to have

Experience with Snowflake, Great Expectations, or dbt-expectations.
Exposure to GCP or Azure.
Familiarity with Terraform and semantic layers.

Culture & Benefits

28 days holiday, bank holidays & 2 volunteer days.
Access to internal training provider – Bauer Academy.
Enhanced Maternity/Adoption, Paternity and Shared Parental Leave Pay.
Opportunity for flexible working.