In this role, you will support the Data Engineering team at Prudential Singapore in setting up the Health Pillar on Azure Data Lake on Cloud. You will develop data pipelines for new sources, real time streaming, data transformations within the Data Lake , CI/CD and data delivery as per the business requirements.
· Build pipelines to bring in wide variety of data from multiple sources within the organization as well as from social media and public data sources.
· Collaborate with cross functional teams to source data and make it available for downstream consumption.
· Work with the team to provide an effective solution design to meet business needs.
· Ensure regular communication with key stakeholders, understand any key concerns in how the initiative is being delivered or any risks/issues that have either not yet been identified or are not being progressed.
· Ensure dependencies and challenges (risks) are escalated and managed. Escalate critical issues to the Sponsor and/or Head of Data Engineering.
· Ensure timelines (milestones, decisions and delivery) are managed and value of initiative is achieved, without compromising quality and within budget.
· Ensure an appropriate and coordinated communications plan is in place for initiative execution and delivery, both internal and external.
· Ensure final handover of initiative to business as usual processes, carry out a post implementation review (as necessary) to ensure initiative objectives have been delivered, and any lessons learned are fed into future initiative management processes.
Who we are looking for:
· Competencies & Personal Traits
· Work as a team player
· Excellent problem analysis skills
· Experience with at least one Cloud Infra provider (Azure/AWS)
· Experience in building data pipelines using batch processing with Apache Spark (Spark SQL, DataSet / Dataframe API) or Hive query language (HQL)
· Knowledge of Big data ETL processing tools
· Experience with Hive and Hadoop file formats (Avro / Parquet / ORC)
· Basic knowledge of scripting (shell / bash)
· Experience of working with multiple data sources including relational databases (SQL Server / Oracle / DB2 / Netezza), NoSQL / document databases, flat files
· Basic understanding of CI CD tools such as Jenkins, JIRA, Bitbucket, Artifactory and Azure Dev-ops.
· Basic understanding of DevOps practices using Git version control
· Ability to debug, fine tune and optimize large scale data processing jobs
Work Experience
· 2-5 years of broad experience of working with Enterprise IT applications in cloud platform and big data environments.
Professional Qualifications
· Certifications related to Data and Analytics would be an added advantage
Education
· Master/bachelor’s degree in STEM (Science, Technology, Engineering, Mathematics)
Language
· Fluency in written and spoken English
