Data Engineer

As a Data Engineer, your role will be to store, process, model and apply data science to make data and insights available for data analytics and business intelligence (BI) systems. You will need to be competent in data assessment and profiling, source system analysis and be able to provide a clear vision on how the data can be processed and interpreted to support the end-use of the data.

The ideal person will come from a Data Engineering or Data Warehousing background (Data Engineer/DW Developer) with Software Engineering, strong DW development and ETL/ELT data pipeline experience.

Key Skills

• Strong data modelling and SQL/database design skills
• Skill and knowledge of ETL/ELT processes
• Strong experience with Python
• Excellent numerical, analytical and statistics skills
• Experience in visualising/presenting data and insights to stakeholders. Utilisation of BI tools such as Looker is a distinct advantage
• Experience working with cloud data warehouses, ideally development within (AWS/Redshift/Azure, GCP or Snowflake experience)
• dbt experience highly advantageous

Responsibilities

• Analyse, organise and prepare raw data for modelling and data analytics
• Architect and help build data systems and pipelines
• Evaluate business needs and objectives
• Combine raw information from different sources
• Explore ways to enhance data quality and reliability
• Identify opportunities for data acquisition
• Participate in the development of analytical reports, including conducting analysis, applying data science techniques, summarising data and interpreting of results

Additional Skills

• JIRA/Asana
• Requirements gathering and documentation skills
• Multiple BI tool experience
• HTML
• Knowledge of Fivetran, Matillion and other ETL/ELT tools

Company Benefits

• Uncapped budget for L&D
• Private Pension
• Private Healthcare
• Bonus Scheme
• Hybrid working
• Early Finish Fridays
• Death in Service Insurance

Interview Process

• Initial intro call with HR Manager (15-20 mins)
• Culture Fit Interview with COO
• Technical Interview with CEO / Head of Engineering / Lead Data Engineer