Analyst, Applied Analytics

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

What will you do?

• Design and implement relevant data models in the form of data marts stored in Operational Data Stores, Data Warehouses or Big Data platforms
• Build data pipelines to bring information from source systems, harmonise and cleanse data to support analytics initiatives for core business metrics and performance trends.
• Perform data profiling to understand data quality and advise practical measures to address such data issues through data transformation and data loading
• Dive into company data to identify sources and features that will drive business objectives.
• Work closely with project manager and technical leads to provide regular status reporting and support them to refine issues/problem statements and propose/evaluate relevant analytics solutions
• Bring your experience and ideas to effective and innovative engineering, design and strategy
• Work in interdisciplinary teams that combine technical, business and data science competencies that deliver work in waterfall or agile software development lifecycle methodologies
• The range of accountability, responsibility and autonomy will depend on your experience and seniority, including: o Contributing to our internal networks and special interest groups o

• Mentoring to upskill peers and juniors What do you need to succeed?
• Possess good communications skills to understand our customers' core business objectives and build end-to-end data centric solutions to address them
• Good critical thinking and problem-solving abilities

Must-have:

• Prior experience building large scale enterprise data pipelines using commercial and/or open source data management tools from vendors such as Informatica, Talend, Microsoft, IBM or Oracle
• Strong knowledge of data manipulation languages such as SQL necessary to build and maintain complex queries and data pipelines
• Practical appreciation of data quality metrics and remediation strategies
• Data modelling and architecting skills including strong foundation in data warehousing concepts, data normalisation, and dimensional data modelling such as OLAP • Undergraduate or graduate degree in Computer science or equivalent

Nice to have:

• Experience with other aspects of data management such as data governance, metadata management, archival, data lifecycle management
• Processing of semi-structured and unstructured data sets such as NoSQL, graph and Hadoop based data storage technologies such as MongoDB, Cassandra, HBase, Hortonworks/Cloudera, Elastic Search and Neo4j using Spark, Splunk or Apache Nifi for batch or streaming data
• Large scale data loading experience moving enterprise or operational data from source systems to new applications or data analytics solutions
• Experience in leveraging on cloud-based data analytics platform such as: o AWS serverless architecture in Lambda on AWS DynamoDB, EMR Redshit o Azure Data Factory or SQL Data Warehouse o GCP BigQuery/BigTable, Cloud Dataprep/Dataflow/Datapro