Data Analyst in Newton Aycliffe - Jackson Hogg

We’re looking for a Data Analyst to help build and scale a modern data capability within a fast-growing e-commerce business.

Working closely with the Head of Data, you’ll play a key role in developing reliable data pipelines, supporting the data warehouse, and turning complex datasets into trusted reporting and insight. Sitting between engineering and analytics, this role is ideal for someone who enjoys both building data foundations and seeing their work directly influence commercial decisions.

Data Engineering & Platforms

• Supporting and improving data pipelines that ingest data from e-commerce platforms, marketing channels, finance systems, and logistics tools
• Helping maintain and evolve the company’s data warehouse and core data models
• Ensuring data is structured, scalable, and fit for analytical use
• Monitoring pipeline reliability, performance, and cost efficiency
• Working with modern data tooling such as cloud data warehouses, orchestration tools, and transformation frameworks

Analytics & Reporting

• Building dashboards and reports covering marketing performance, customer behaviour, operations, and financial metrics
• Translating business questions into clear data models and visualisations
• Supporting the rollout of self-service reporting across teams
• Maintaining consistency in KPI definitions and reporting logic

Business Collaboration

• Working closely with stakeholders across marketing, e-commerce, operations, supply chain, and finance
• Producing ad-hoc analysis to support trading decisions, campaigns, and operational improvements
• Turning complex datasets into clear, actionable insights

• 2+ years’ experience in data engineering, analytics, or a similar role
• Working knowledge of SQL and data modelling principles
• Experience with cloud data warehouses (e.g. Snowflake, BigQuery, Redshift)
• Dashboarding experience using tools such as Power BI, Tableau, or Looker
• Strong analytical thinking and problem-solving skills
• Comfortable working with non-technical stakeholders

• E-commerce, retail, or FMCG experience
• Exposure to marketing data (paid media, email, marketplaces)
• Experience with tools such as dbt, Airflow, or Fivetran
• Basic Python or R for analysis or transformation
• Interest in customer analytics, forecasting, or attribution