Work with stakeholders including customers, partners and colleagues on data-related technical issues and support their data infrastructure needs;
Work closely with data scientists to solicit data requirements to support modeling works;
Design, develop, document, manage and maintain data models, ETL processes, data warehouse, data management and pipeline solutions for large volume of structured/unstructured data from disparate sources and with different latencies (e.g. on-demand, batch, real-time, near-real-time);
Define, monitor and report SLAs for data pipelines and data products;
Understand data security and governance standards or requirements to implement solutions that ensure adherence to these standards or meet such requirements;
Drive/execute data quality assurance practices; and
Support data management solutions pre-sales initiatives, proposal development and provide post-sales support.
Requirements
Technical expertise in:
Relational/non-relational/NoSQL database and enterprise data warehouse/mart;
Big data technologies e.g. Hadoop, Spark, Hive, HBase etc.;
Data ingestion technologies e.g. Flume, Kafka, NiFi etc.; and
Scripting, programming and software development using e.g. Java, C/C++, Python, R, MATLAB, Scala, SQL etc. for Windows or Linux environments.
Experience in master data management, data governance, data lifecycle management etc.;
Experience in designing, documenting, implementing and supporting data management solutions;
Experience in using software engineering best practices in development, programming, testing, version control etc.;
Knowledge of data privacy and security assurance; and
Knowledge of machine learning, computer vision and large language models will be advantageous.
Excellent written and verbal communications skills;
Highly organised, motivated, independent and resourceful team player;
Strong analytical thinking, interpersonal and problem-solving skills; and
Able to work productively in a matrix reporting and fast-paced environment