In the context of team expansion, Neurones IT Asia is currently looking for a Senior Data Consultant for one of our clients in Singapore.
Role
- Embed themselves within business teams to identify opportunities to apply IT solutions to their problems of gaining insight from their data.
- They will need to take ownership of their own learning to gain a deep understanding of how the business teams operate. This is to help the business teams understand how technology can help them do more with their data.
- Work collaboratively and iteratively directly with the business stakeholders to design, develop, and test BI solutions.
- Be expected to take ownership of the architecture of any systems developed and in choosing an appropriate technology stack.
- Prevent the development of a fragmented application estate by working closely with the Solution Architect to ensure that BI solutions form part of a coherent data strategy across the organization.
- Collaborate with other organizational efforts around Data Analytics and Market Data Management to take advantage of any synergies.
- Work closely with other IT architect stakeholders to ensure that solutions are in alignment with IT strategy around business architecture, infrastructure architecture, and technology.
- Work with the IT Operations/Infrastructure team to deploy solutions into the client's IT infrastructure in a sustainable way.
- Be expected to deliver a robust, production-standard system using modern software engineering techniques including automated unit/integration testing, continuous integration, and automated deployment.
- Be comfortable with agile delivery modes such as Scrum or Kanban but should also be flexible to work with whichever delivery approach works best for the business stakeholders.
Technical SkillSet
- Having solid experience in data modeling, data warehousing, SQL Server database design and development (SQL, relational and dimensional modelling) Analytical querying using technologies such as SSAS cubes or columnar data stores, Python
- ETL tools such as SSIS, Alteryx, Azure Data Factory · Building data pipelines using code e.g. Pyspark Modern cloud-based data architectures and technologies such as Data Lake, Delta Lake, Data Lakehouse e.g. Azure Data Lake Gen 2, Azure Delta Lake Lakehouse architecture using Databricks, Hudi or Iceberg
- NoSQL using CosmosDB, MongoDB, DynamoDB etc.
- Python scripting, including data engineering and machine learning libraries · Scripting languages such as Powershell, bash, DAX, M-language etc. (Note - We primarily use SQL, Pyspark and Python in our day-to-day work along with some coding around DAX, Bash, Powershell and other scripting languages. )
- Distributed computing mainly around Spark § Big data files formats e.g. Parquet, Avro, ORC etc.
- Big data technologies such as Hadoop, Hive, Map-Reduce, Partition design, performance tuning in Spark etc.
