Mid-Level Data Engineer (GCP) (IRC270767)

Job Description

Familiarity with Google Cloud Platform, including BigQuery, Cloud Composer(Airflow), Compute Engine, and Monitoring.
Strong proficiency in Python, including experience in building, testing, and deploying robust ETL/ELT pipelines in production
Experience developing data quality frameworks, including automated tests, cross-dataset validations, and anomaly detection across diverse data assets
Advanced SQL skills, including data modeling (star/snowflake/3NF), optimization, and writing performant queries tailored to BigQuery’s slot-based execution model
Solid working knowledge of DBT, including incremental models, testing, documentation, and advanced features like custom macros
Demonstrated ability to optimize BigQuery workloads through partitioning, clustering, materialized views, and cost-aware development practices
Experience working with ETL orchestration tools, ideally Cloud Composer or similar frameworks (Kestra, Dagster,etc.)
Hands-on experience consuming and managing APIs for data extraction.
Exposure to Site Reliability Engineering (SRE) best practices, including ticket triage, incident management, and documenting runbooks/SOPs
Familiar with Git and modern software development workflows, including pull requests and code reviews
Comfortable working in an agile team environment, with the ability to multitask and reprioritize based on changing project needs
Clear and effective communication skills, with the ability to engage technical and non-technical stakeholders alike

Job Responsibilities

Designing, building, and maintaining scalable, reliable data pipelines using Python,SQL, DBT, and Google Cloud Platform (GCP) services like BigQuery and Cloud Composer.
Contributing to the development and evolution of our data quality framework, ensuring robust automated testing and cross-dataset validation across all critical data assets
Writing and optimizing advanced SQL to power data models, analytics, and reporting pipelines, with a focus on performance and efficiency within BigQuery
Developing and maintaining DBT models, including testing, documentation, incremental loading strategies, and the creation of reusable macros
Supporting day-to-day incident and ticket resolution, including root cause analysis and documentation of runbooks/SOPs to drive platform reliability
Working with APIs and external data sources to extract, normalize, and integrate new datasets into the platform
Participating in agile ceremonies (stand-ups, retros, planning), contributing to sprint goals and helping support the wider team objectives
Actively contributing to code reviews, documentation, and peer learning—helping to raise engineering standards and share knowledge within the team
Monitoring system health and pipeline performance using GCP-native tools and dashboards, and proactively identifying opportunities for cost or performance optimization

Bonus points for

GCP Data Engineer certification
Prior experience in media, marketing, or digital advertising analytics
Experience implementing data quality frameworks and governance tools
Familiarity with cost optimization strategies for BigQuery and other GCP services

Department/Project Description

WPP is transforming its global data infrastructure to deliver faster, more scalable, and more intelligent analytics capabilities. As part of this journey, we're hiring a Technical Lead, Data Engineering to manage the technical delivery and operational resilience of our core data platform.

This role sits at the intersection of engineering leadership, platform reliability, and architecture — helping us ensure that data flows are healthy, scalable, and ready for production. You’ll work across project delivery, production support, and platform enhancement initiatives while mentoring a growing team of engineers.