Data Architect - Big Data, AWS, NoSQL
This is a key role that will be accountable for the development and operations of a large data transformation in particular supporting users in the finance department. You will work as part of a cross-functional agile delivery team, including analysts, architects, big data engineers, machine learning engineers, and testers.
The individual will seek to identify improvements and efficiencies, while utilising new technologies and existing tools.
The core responsibilities and objectives of the role include, but are not limited to:
- Work as part of the CDO to ensure data models and architectural patterns are aligned to user and business requirements.
- Design and lead the implementation of new core data platforms to help with the adoption of modern Data solutions
- Champion and consult with other teams across the organisation to advocate the CDO function and the architectural solutions being generated.
- Work closely with the data engineering team to design and implement enterprise-grade pipelines for data.
Suitable candidates will need to have the following skills and experience:
- Experience with data modelling (star, snowflake, etc schemas) and performance optimisation of data tables.
- Experience with working with internal customers to understand their use cases and ensure architecture conforms to their needs.
- Experience with both analytical and transactional processing databases
- Experience building enterprise grade data pipelines (ETL and ELT)
- Experience with Cloud-native data services, such as AWS Athena, Redshift, Kinesis/Managed Kafka, DynamoDB, Glue, Lambda, S3
- Experience building and championing adoption of common architectural patterns and driving their adoption
- Solid understanding of Enterprise patterns and applying best practices when integrating various inputs and outputs together at scale.
- Knowledge of software best practices, like Test-Driven Development (TDD) and Continuous Integration (CI)
- Decent knowledge of NoSQL and Big Data tools (Hadoop, Hive, MongoDB, DynamoDB, Presto)