Senior Analytics Engineer: Data Products & Looker Lead

Checkout Ltd; Greater London; Hybrid; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Hybrid working

Job summary

Checkout.com is seeking a Data Analytics Engineer to enable key product insights and establish a single source of truth for North Star metrics. You will own multiple data products end-to-end, from design to implementation to operationalization.

You will build scalable data models and analytics pipelines, collaborating with product managers and data scientists to shape the product's evolution. Hybrid working applies, with a London focus.

Qualifications

• Proven delivery experience in data, BI or analytics engineering.
• Hands-on data modelling and data warehousing skills in large-scale environments.
• Experience with analytics SDLC, version control, testing, and CI/CD.
• Excellent SQL and data transformation skills (dbt or equivalent).
• Familiar with Snowflake/AWS/GCP/Azure cloud platforms.
• Passion for analytics across sales, finance, customer, marketing or product domains.
• Attention to data quality and governance practices.

Responsibilities

• Design and implement high-performance, reusable data models for the data warehouse using dbt and Snowflake.
• Design Looker structures to enable self-serve analytics across the organization.
• Collaborate with data analysts and business teams to provide data-ready analyses and reports.
• Continuously discover, transform, test, deploy and document data sources and models.
• Champion data quality, testing, documentation, and coding best practices in governance.

Skills

Data modelling

Data warehousing

SQL

CI/CD

Analytical mindset

Tools

dbt

Looker

Snowflake

AWS

GCP

Job description

Checkout.com is seeking a Data Analytics Engineer to enable key product insights and establish a single source of truth for North Star metrics. You will own multiple data products end-to-end, from design to implementation to operationalization.

You will build scalable data models and analytics pipelines, collaborating with product managers and data scientists to shape the product's evolution. Hybrid working applies, with a London focus.