Senior/ Data Engineer (Multiple openings)

at  TALENTSIS PTE LTD

TECHNICAL KNOWLEDGE/SKILLS/COMPETENCIES:

• 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.

SOFT SKILLS:

• 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.
  (EA Reg No: 20C0312)
  Only shortlisted candidates will be notified.
  Please email a copy of your detailed resume to drew@talentsis.com.sg for immediate processing

• 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.
• Support data management solutions pre-sales initiatives, proposal development and provide post-sales support.