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Azure Data Engineer

3 weeks ago

Singapore PSA International Full time

**Job Type**:Full TimeAs a member of #TeamPSA, you will be part of a diverse and global team at the forefront of creating cargo solutions to enable more agile, resilient and sustainable supply chains. Experience first-hand and drive supply chain transformation from Singapore and through PSA’s global network of ports, logistics and supply chain solutions. Alongside, we can move the world
- **_Develop Your Potential:_** We emphasise and offer exciting rotations, learning and development opportunities, which will fuel your career aspirations and complement your business exposure across our global network.
- **_Diverse, Equal Opportunity:_** We build a sustainable work culture where all our people feel welcome, valued, respected and able to express their ideas and beliefs freely. We believe that diversity of thought and approaches in our workplace makes us stronger as a team.
- **_Competitive Compensation & Benefits:_** We are committed to recognising and rewarding your contributions to the business. Our benefits packages aim to improve your quality of life by providing support for medical, dental, recreation, among others.

You will be engaged as a Data Engineer in PSA Group Data For Excellence (DFE), supporting PSA’s Data Analytics initiatives and PSA Global Data Analytics Platform (GDAP). Besides creating and maintaining data pipelines, data models; enhancing GDAP features; you will work with other DFE members to promote data culture and data analytics competency within PSA.

**Job Description**:

- Work with PSA business units globally to set up their data analytics needs within GDAP
- Enable the timely availability of good quality data to facilitate data-oriented management decisions
- Work with new data sources from around the world to provide data to our Global Data Analytics Platform built on Azure Cloud
- Implement automated Data Quality measures to sieve out bad quality data for timely rectifications by data sources
- Design, construct and maintain Datawarehouse models to support PSA global, regional and local business units data analytics needs.
- Create and maintain data pipelines to transform and load data from data lake into Datawarehouse models
- Create and maintain data science sandbox, machine learning tools, Databricks, data marts, data catalogue, data lineage, etc
- Continuous enhancement of GDAP to keep the platform relevant and ready
- Work and collaborate with PSA data analytics team at all stages of CRISP-DM Methodology
- Align to PSA data analytics policy, standards and best practices and document as required
- Jointly organize data analytics workshops and data seminars to promote data culture and data analytics competency within PSA

Technical Requirements:

- Degree from a recognised university, preferably in Data Analytics or Computer Science domain;
- Must have at least three years hands-on experience as a Data Engineer including at least two years using Microsoft data tools;
- Must have knowledge of data warehouse concept (Star, snowflake or data vault) methodology and experience in designing data warehouse dimensional modelling;
- Must have hands-on experience in Azure Data Factory, Azure Synapse Analytics / Datawarehouse, Azure Analysis Services and Python;
- Preferably with relevant certifications from Microsoft including Azure Data Engineer Associate;
- Preferably with hands-on experience in using Semarchy xDM;
- Knowledge of Azure Databricks, Azure HDInsight or Azure OpenAI or Azure AI Services or Power BI or Microsoft Power Platform or R or.Net or C# or NoSQL or open source data analytics software will be advantageous.

Soft Skills Requirements:

- Strong project management skills;
- Analytical, meticulous, team player;
- Strong written and oral communication skills in English. Ability to communicate in additional languages is added advantage;
- Strong interpersonal skills to liaise effectively with users and stakeholders; overcoming challenges of language, cultural and time zones;
- Ability to work under pressure towards fixed deadlines without jeopardizing standard of work.