Decades of data underpins our business. As a shared service function, the analytics department plays a crucial role ensuring our stakeholders needs are being met – be that for commercial divisions, finance, product, marketing or operations. The current main outputs are; enabling self-service reporting and analysis, creating new or ad hoc reports and dashboards, retrospective analysis and automation of it, as well as forecasting.
The team has successfully set up our data warehouse but there are many improvement-based projects to complete such as; refining existing reports, bringing in new data sources to the warehouse and extracting new insights.
Reporting to the Head of Engineering, we are looking for a savvy Data Engineer to join our Business Intelligence and Data team. The hire will be responsible for expanding and optimizing our data warehouse and data pipeline architecture, as well as optimizing data flow and collection. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing and expanding our company’s data architecture to the pave way for advanced analytics, such as the introduction of Data Lakes.
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Support the engineering leadership team in defining the technology roadmap to underpin advanced analytics and data science.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
You should also have experience using the following software/tools:
- Experience with Azure Data Factory, Azure Analysis Services, PowerBi, and DAX.
- Experience with relational SQL and NoSQL databases.
- Experience with MS SQL Server and Transact-SQL.
- Experience with Google Analytics.
- Experience with AWS/Azure cloud services.
- Experience with Python, R and C# would be advantageous.
- Knowledge and experience of architectures to support advanced analytics and data science would be advantageous.