Senior Data Engineer
1 week ago
Our Company
Gentco Logistics is a leading international liquid chemical logistics provider with three core business units: chemical tankers (5th largest fleet globally), chemical tank containers (2nd largest fleet globally), and terminal storage tanks. Our global headquarters are in Shanghai, China, supported by a regional headquarters in Singapore and 40 operational offices across six continents. Gentco Logistics is wholly owned by the Junzheng Group (ticker 601216.SH).
The Opportunity
The Senior Data Engineer position is a part of the Global IT Department, which is directly overseen by the Group’s CIO. Our team currently comprises over 60 IT, software, and data professionals primarily based in Shanghai and Moerdijk (the Netherlands). With our IT presence in Singapore rapidly expanding, we are excited to invite you to join our team As a Senior Data Engineer in our Singapore office, you will have the unique opportunity to join a newly established data engineering team while being supported by our existing data engineering talent in Shanghai and Moerdijk. This role offers excellent career progression as you will take on a pivotal role in establishing and growing a local team in Singapore.
Job Responsibilities:
· Take ownership of the implementation and maintenance of critical pieces of our Azure ETL pipeline and data warehouse (ADF/DBT/Apache Airflow/AKS/Databricks)
· Assist in the maintenance of an existing data infrastructure (Azure SQL MI)
· Assist in the design and architecting of ETL/ELT pipelines, data schemas/models, and data marts for business users.
· Ensure the reliability and availability of core data infrastructure with proper monitoring and alerting systems to guarantee continuous data delivery to the business.
· Take ownership of data quality and governance. Collaborate with business and IT teams to establish and meet data standards, including developing automated data checks and data quality monitoring dashboards.
· Promote a culture of organizational learning by facilitating knowledge sharing and implementing best practices in documentation.
· Stay updated with current industry best practices and trends, and evaluate technical decisions at a business level.
· Provide leadership, guidance, and oversight to junior data engineers.
Requirements:
· Bachelor's or Master's degree in Computer Science or a related engineering field from a technical university.
· 4+ years of experience in data engineering
· 2+ years of experience with Azure data infrastructure (e.g. ADF, DBT, AKS, IaC).
· 1+ year of experience with Agile/DevOps tools (Git, Jira).
· Deeply knowledgeable of data warehousing best practices, especially in the Azure cloud environment, with a strong commitment to staying current with industry trends and future advancements.
· Thoroughly familiar with the relevant trade-offs within different data modelling schemas (e.g. 3NF, star, snowflake, data vault) and storage architectures (e.g. data warehouse, data lake, data lakehouse)
· Highly motivated, with a proactive approach to project ownership and accountability for outcomes and timelines. Committed to continuous personal growth and development within the organization.
· Fluency in both written and spoken English and Mandarin is highly desirable to effectively liaise with Chinese-speaking clients and counterparts, understanding their technical requirements.
Desirable skills
· Proven experience with cloud infrastructure at a global scale, with knowledge of navigating global data regulations at a technical level.
· Experience with master data management using modern MDM tools, ideally at a global scale and/or in a cloud environment.
· Background in the shipping/maritime or chemicals industry.
· Previous leadership experience as a lead engineer.
· Experience with PowerBI and Plotly.
Tell employers what skills you have
Microsoft Azure
Azure
Big Data
Pipelines
Azure DevOps
Hadoop
Azure Data Factory
ETL
Data Quality
Reliability
Data Engineering
PowerBI
SQL
JIRA
SQL Server
Accountability
Java
Master Data Management
Data Warehousing
Databases
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