Business Intelligence Engineer
Location: London
Length: 9 Months
Rate: From £350 - £400 p/d PAYE
Hours:
9am-6pm
This client is a top 5 tech giant with a global retail operation, video streaming platform, and has a big imprint in web services. This is a hybrid role, so you will split your time between home office and the clients offices in central London. On-site you will be able to access their amazing facilities and quirky working spaces.
Job Description:
As a BIE, you will own partnering with data engineering and software engineering teams to drive best-in-class business intelligence solutions at scale. You will work with structured and unstructured data sources to develop deep business insights and architect key business metrics. You will partner with scientists to build forward-looking data experimentation, predictive modelling, and machine learning algorithms. The role is cross functional and will require working closely with a wide variety of stakeholders including senior members across engineering, product, business leadership, and economics/data science teams.
Key job responsibilities:
- Drive the design, development, and maintenance of innovative and scalable intelligence solutions across the organization, with the highest standards of analytical rigor and data integrity.
- Develop domain expertise and drive major contributions to our data and research roadmap. Leverage SQL, ETL, Redshift, and other available tools to uncover deep business insights, trends, and opportunities to innovate on behalf our customers.
- Partner with data engineering to build best-in-class data architecture and pipelines to support analytics needs.
- Translate ambiguous business problem statements into actionable analytical solutions. Manage large scale data requests and projects to define requirements, manage timelines, and coordinate activities with other involved team members.
- Partner with scientists to translate business insights and trends into experimentation and testing, and modelling.
Basic qualifications
- 3+ years of analysing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modelling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modelling
- Experience with SQL
- Experience in the data/BI space
Preferred qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets