Senior Data Analytics Engineer

Jobs homepageCurrent openings Back Senior Data Analytics EngineerLondon, United Kingdom · Permanent · On siteOverviewApplicationAbout this job Apply Share job Job description As a Senior Data Analytics Engineer at Beauty Pie, you will be responsible for designing, developing, and maintaining robust data pipelines and analytics solutions that empower stakeholders to self-serve where possible. You will collaborate closely with data analysts and business stakeholders to ensure the availability and accuracy of data needed for decision-making. Your expertise in data engineering, analytics, and software development will be crucial in driving our data strategy forward.Beauty Pie is a subscription-based e-commerce retailer, and we have recently migrated our storefront to Shopify. This is an exciting time to join! You will play a key role in building out and maturing our data platform within the Shopify ecosystem, integrating data from Shopify and its surrounding ecosystem of tools and platforms.We move fast, but deliberately. We'd rather pilot something quickly and learn from it than spend weeks perfecting a plan. If you thrive in an environment where priorities shift, new ideas are tested rapidly, and you're trusted to use your judgement, you'll fit right in.We are an AI-first team. We actively use AI tools such as Claude Code to accelerate our development workflow, and we expect you to embrace AI-assisted development as a core part of how you work. Equally important is your ability to be the human in the loop by critically reviewing AI-generated output, applying sound engineering judgement, and knowing when to trust vs challenge. Job requirements Significant experience in data engineering, analytics engineering, or a related role.Recognised subject matter expertise in at least one area of the data stack, with a strong working knowledge across the rest.Passionate about helping stakeholders to solve business problemsExcellent SQL and data transformation knowledgeExperience with dbt or similar data modelling frameworksStrong Python skillsExperience with Snowflake or similar cloud data warehouses (Databricks, BigQuery)Knowledge of data warehousing concepts, Kimball, Inmon & Data VaultExperience with data visualisation tools e.g. Looker, Lightdash or TableauProven experience in data ops (CI/CD, testing, orchestration, observability)Ability to lead cross-functional technical initiatives and influence without authorityExperience with infrastructure as code (Terraform) is a plusExperience with workflow orchestration tools such as Airflow is a plusExperience with event-driven data architectures and real-time analytics is a plusExperience working with Shopify or e-commerce data is a plusStrong communication and collaboration skills, with the ability to adapt your style for different audiences including senior stakeholders.Our tech stack: Cloud: AWSInfrastructure as Code: TerraformOrchestration: Airflow (MWAA)Data Warehouse: SnowflakeData Modelling: DBT Data Ingestion: DLT (Data Load Tool)Language: Python Job 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.Champion continuous improvement by proactively identifying bottlenecks, introducing process changes, and automating...