NTUC INCOME INSURANCE CO-OPERATIVE LTD
Consulting, Information Technology, Insurance, Professional Services, Others
Permanent, Full Time
S$5000 - S$9500
2 words best describe the Data Analytics journey in Income –
Incremental & Impactful.
The fact that the Analytics team has grown to a 10 member team in just 4 years, is one of the reflections of this journey. To be “a data driven organization” is one of the key themes on which the organisation aims to achieve Goal 2025. Consequently the role of advanced analytics has to scale up to be able to deliver significant business outcomes.
We are looking for a talented Data Engineer that will focus on :
Design, develop, and operate data ingestion and integration pipelines to provide high quality datasets for analytical and machine learning use-cases
Collaborate with other data engineers, analysts, data scientists, product specialists, and other stakeholders to build well-crafted, pragmatic and elegant engineering solutions.
Recommend and implement ways to improve data reliability, efficiency, and quality
Manage existing runs and deployment of ML model pipelines
Driving enterprise data foundation requirements of Data Warehousing, Data Lake
Acquiring, storing, governing and processing large datasets of structured/unstructured data
Communicate with users, other technical teams, and management to collect requirements, identify tasks, provide estimates and meet production deadlines
At least 4 years of experience in data engineering with relevant experience in big data ecosystem
A bachelor's degree in Computer Science or equivalent
You are passionate about technology and are always looking to improve yourself
Interested in being the bridge between engineering and analytics
Knowledgeable about system design, data structure and algorithms
Good knowledge of big data technology landscape and concepts related to distributed storage and computing
Experience with big data processing tools such as Spark, MapReduce, etc.
Experience with batch and ETL jobs to ingest and process data
Experience with Data Warehouses such as Redshift, BigQuery, Snowflake, etc.
Experience with Cloud environments such as AWS, GCP, Azure
Experience with other NoSQL databases such as Elasticsearch, DynamoDB, Cassandra, etc.
Programming experience with SQL, Python, Java, Scala
Experience with event sourcing systems such as Kafka, Kinesis and the associated APIs such as Kafka Connect, Kafka Streams, KCL, Spark Structured Streaming, etc.
Experience or willingness to work on DevOps practises such as infrastructure-as-code, data-pipeline-as-code
High-level understanding of Data-science model development topics such as training and deployment
Closing on 19 May 2021orview more job listings from this company