Senior Data Engineer (Reporting & Analytics)

What you'll be responsible for

• Driving Data Architecture: Design and build a scalable, end-to-end data architecture on GCP. This includes creating robust and efficient data models in our data warehouse, defining data flows, and ensuring the infrastructure is optimised for high-volume, near real-time data processing.


• Building & Optimising Data Pipelines: Develop, deploy, and manage resilient data pipelines for large-scale data ingestion and transformation. You will be hands-on with GCP DataStream to implement CDC and orchestrate complex SQL-based transformation workflows with Dataform.


• Solving Complex Data Challenges: Tackle and resolve complex performance bottlenecks across the entire data stack. This involves optimising intricate calculations, tuning database performance, and ensuring the efficiency of our data models to support low-latency queries from Looker.


• Upholding Data Quality & Integrity: Champion and implement best practices for data quality, testing, and governance. You will establish robust data validation checks and build out CI/CD pipelines for all data processes to ensure the accuracy and reliability of our reporting.


• Technical Leadership & Mentoring: Provide technical guidance and mentorship to other engineers on data engineering best practices. You will lead technical decisions, evaluate trade-offs, and foster a culture of data excellence within the squad.


• Stakeholder Collaboration: Work in close partnership with product managers and front-end engineers to deeply understand user requirements and translate them into effective data solutions that power our embedded analytics features.

Experience and skills we look for

• Proven Experience in Data Engineering: A strong track record of designing, building, and optimising data-intensive systems and large-scale ETL/ELT pipelines.


• Expertise in the Modern Data Stack: Deep, hands-on experience with cloud-based data platforms, with a strong preference for Google Cloud Platform (GCP). AWS knowledge a plus, but not essential.


• Specialised GCP Skillset: Demonstrable, practical experience using GCP Datastream (or similar technology) for Change Data Capture (CDC) and Dataform (or similar tools) for developing and managing data transformations. Proficiency with BigQuery is essential.


• Strong Data Modeling Skills: Extensive experience designing and implementing data models (e.g., dimensional modeling, data vault) optimised for analytical workloads and BI tools.


• Advanced SQL & Programming: Expertise in advanced SQL for complex data manipulation and analysis, coupled with proficiency in a programming language like Python for automation and scripting.


• Performance Tuning & Optimisation: A proven ability to diagnose and resolve performance issues within data pipelines and databases. You understand query optimisation, indexing, and partitioning strategies.

Additional Skills that set you apart

• BI & Data Visualisation: Experience working with modern business intelligence tools, with specific experience using or building solutions for Looker.


• Complex Calculations: Experience in environments that require translating complex business logic or financial calculations into accurate and performant SQL.


• Secure Cloud Environments: Experience working with data services in highly secure or compliant environments is a plus.


• CI/CD for Data: A solid understanding of CI/CD principles and tools (e.g., Git, Jenkins, GitLab CI) applied to data pipelines and infrastructure-as-code (Terraform familiarity a plus).