AddressAbout the Role
SSP are world leaders, but in many ways the Data and Analytics function feels like a start-up, with a twist. There’s the buzz of innovative projects, the thrill of shaping compelling customers experiences, the chance to surprise and stretch yourself in response to a fresh challenge. And then there’s all the resources, technology and high profile projects of a major corporate entity. Crucially, we also offer the benefit of clear career progression. SSP are undergoing a technology transformation with board support for IT investment. We have a portfolio of strategic priorities and a clear vision. We require a Senior Data Engineer to join Group Digital and Technology as part of the Analytics team to become a member of a new engineering practice delivering strategic analytics and insight solutions for the SSP business. You will be designing, implementing and improving data pipelines as we migrate our SQL 2016 environment into the Azure Cloud. Building out Net New API solutions and digital pipelines. You will work in conjunction with our Data Analyst and QA as you engineer 21st century digital solutions. Beyond just the Power BI Univariate and into the multivariate modelling world. We are modernising our core systems of record and enabling digital and technology innovation. A key aspect to this journey is the data driven enterprise, with data management, analytics and insight and intelligent solutions as fundamental building blocks. This role will need to develop high quality data, BI and ML/AI solutions primarily with Microsoft Azure data and BI services and Microsoft Power BI.
Main Duties
- Designing and delivering data pipelines
- Designing and building Azure Data Factory data flows
- Ingesting data into an Azure Data Lake
- Designing data models for large datasets, including creating dimensional multivariate models as outputs for ingested data
- Exposure to non-relational data storage such as mongo DB type design
- Experience in SQL Server Integration Services (SSIS)
- Good experience with ETL
- SSIS, SSRS, T-SQL (On-prem/Cloud)
- Experience with NoSQL type environments, Data Lakes, Lake-Houses (Cassandra, MongoDB or Neptune)
- Have experience with Python
- Knowledge of statistics principles necessary to interpret data and apply models. For example, knowledge of errors and confidence intervals to understand whether a relation seen in the data is real
- Exposure to high performing, low latency or large volume data systems (i.e. 4 billion+ records, terabyte size database)
- Work within a continuous integration environment with automated builds, deployment and unit testing
Essential
- SQL, Python, R or other similar language
- An interest in machine learning engineering or a desire to skill up
- Retail, Food & Beverage or Hospitality industry experience
- Experience using data within an analytics environment from core enterprise solutions including Oracle Simphony, SAP S4, SAP SuccessFactors
Desirable
- Multi International Geo experience
- An interest in data science, ML and AI
- Be passionate about food and drink
