Your impact
As an AWS Data Analyst, you will play a key role in working with customers to understand their business requirements, map these to their data capabilities, liaise with our internal Data Engineers to design and build elegant solutions, then partner with our customers to deploy those solutions in a way that allows them to turn data into insight. You will have 2-3 years’ experience working as a Data Analyst (or similar role) on data-related solutions using AWS, and will be comfortable working with business analysts, data visualisers, data engineers and data scientists, to enable customers to solve their data-related challenges.
You will relish the opportunity to innovate, evolve and challenge existing assumptions and to develop the data-related requirements that feed into the design of solutions that solve real-world problems for customers. Your experience with large-scale data challenges and ability to analyse them as input into reliable, scalable cloud-based solutions, will see you thriving in this role!
Expectations
Technical Requirements:
2+ years of:
- Hands on, practical experience, in and around data-related solutions
- AWS experience
- A basic understanding of software development tools and methodologies
- Data analysis experience
- Experience producing quality documentation and written communications
Familiarity with DevOps tools such as Github, GitLab, BitBucket, Azure DevOps
A basic understanding of Infrastructure as Code, especially AWS CloudFormation.
Some programming skills in one or more of the following languages: R, Python, Java, Node.js, .Net.
Understanding of SQL, ER diagrams, and data dictionaries to understand and enable querying of data.
Understanding of Business Intelligence tools including PowerBI, AWS QuickSight, and Tableau.
A basic understanding of real-time or batch ingestion and transformation pipelines.
Familiarity with data storage format types such as JSON, AVRO, Parquet, ORC.
Understanding of fundamental data concepts including databases, data schema, data classification, data security, data governance, data analysis, data transformation, data engineering and data science.
Exposure to container technology, especially Docker.
A basic understanding of fundamental networking concepts.