AI-Driven Data Analytics Engineer for Shopify Platform

Beauty Pie; Greater London; Hybrid; GBP 85,000 - 120,000; Full time

Benefits offered by this job

Hybrid work in London

Beauty Pie+ membership

25 days holiday + birthday off

Flexible bank holidays

Parental leave equal for all

Job summary

Beauty Pie is seeking a Data Analytics Engineer in London to design, build, and maintain robust data pipelines and analytics solutions that empower stakeholders to self-serve. You will collaborate with data analysts and business stakeholders to ensure data availability and accuracy for decision-making.

You will help mature our data platform within the Shopify ecosystem, integrating data from Shopify and related tools.

Qualifications

• Solid experience in data engineering, analytics engineering, or a related role.
• Depth of subject matter expertise in at least one area of the data stack, with a good working knowledge across the rest.
• Strong SQL and data transformation knowledge
• Experience with dbt or similar data modelling frameworks
• Solid Python skills
• Experience with Snowflake or similar cloud data warehouses (Databricks, BigQuery)
• Good understanding of data warehousing concepts such as Kimball, Inmon or Data Vault
• Experience with data visualisation tools e.g. Looker, Lightdash or Tableau
• Practical experience with data ops practices (CI/CD, testing, orchestration, observability)
• Ability to communicate concepts clearly to both technical and non-technical audiences
• Experience with infrastructure as code (Terraform) is a plus
• Experience with workflow orchestration tools such as Airflow is a plus
• Experience with event-driven data architectures and real-time analytics is a plus
• Experience working with Shopify or e-commerce data is a plus
• Strong communication and collaboration skills, with the ability to influence others and work effectively across teams.

Responsibilities

• Design, build, and maintain scalable data pipelines to support various data analytics and self-serve needs.
• Develop and implement ELT (Extract, Load, Transform) processes to integrate data from multiple sources into our data warehouse.
• Ensure data quality, consistency, and reliability through rigorous testing and validation procedures.
• Collaborate with analysts to understand data requirements and deliver actionable insights.
• Optimise and tune SQL queries and database performance to handle large volumes of data efficiently.
• Create and maintain documentation related to data architecture, processes, and workflows.
• Build observability into data pipelines and models from the outset including monitoring, alerting, logging, and data quality checks so issues are detected early rather than reported by stakeholders.
• Drive continuous improvement by proactively identifying bottlenecks, suggesting and implementing process changes, and automating repetitive tasks to help the team move faster and more efficiently.
• Stay up-to-date with emerging technologies and best practices in data engineering and analytics.
• Work closely with cross-functional teams to align data initiatives with business goals and objectives.
• Contribute to technical discussions and decisions, analysing challenging problems and proposing well-reasoned solutions.
• Support and guide less experienced team members, sharing knowledge and helping to raise standards across the team.

Skills

SQL

Python

dbt

Snowflake

Airflow

Terraform

Looker

Tools

DBT

Airflow

Terraform

DLT (Data Load Tool)

Looker

Snowflake

Job description

Beauty Pie is seeking a Data Analytics Engineer in London to design, build, and maintain robust data pipelines and analytics solutions that empower stakeholders to self-serve. You will collaborate with data analysts and business stakeholders to ensure data availability and accuracy for decision-making.

You will help mature our data platform within the Shopify ecosystem, integrating data from Shopify and related tools.