全职 Data Engineer 工作, 薪水 up to SGD 6,000, ZENITH INFOTECH (S) PTE LTD. Islandwide (Singapore) 公司招聘中 - Ricebowl

Job:

• Own the design, development, and scaling of our data platform and pipelines.

• Lead a small team of data engineers, work closely with Data Science, Analytics, and Product, and ensure our data is reliable, scalable, and accessible for decision-making and ML products.

• Be hands-on with architecture and coding, while also mentoring engineers and setting engineering standards.

Role:

• Design and implement scalable, reliable, and cost-effective data pipelines and data platforms.

• Build and maintain ETL/ELT pipelines, data models, and APIs using Python, SQL, and modern cloud tools.

• Own data ingestion, storage, transformation, orchestration, and monitoring in cloud environments.

• Guide engineers, conduct code reviews, and drive best practices in data engineering.

• Partner with Data Science, Analytics, Product, and Business teams to translate requirements into technical solutions.

• Drive end-to-end delivery of data projects from requirements gathering to production deployment and support.

• Implement testing, monitoring, and data quality frameworks.

• Enforce data security, privacy, and compliance standards.

• Optimize pipeline performance, cost, and reliability.

• Troubleshoot production issues.

Requirements:

• Masters or Degree in Computer Science, Engineering, Mathematics, or related field.

• Equivalent practical experience will be considered.

• Has at least 6+ years in data engineering, with 2+ years in a lead/senior role.

• Strong in Python and SQL. Experience with PySpark is a plus.

• Hands-on experience with AWS, GCP, or Azure. Services like S3/ADLS, BigQuery/Redshift/Snowflake, Airflow, Kafka, DBT.

• ETL/ELT Tools: Informatica PowerCenter / Informatica Intelligent Cloud Services (IICS).

• Experience with data integration, mappings, transformations, and workflow orchestration in Informatica.

• Strong experience with dimensional modeling, data warehousing, and lakehouse architectures.

• Experience with Airflow, Prefect, or similar workflow tools.

• Engineering practices: CI/CD, Docker, Git, Infrastructure as Code, unit testing.

• Good to Have: Kafka, Spark Streaming, Flink; Databases: PostgreSQL, MongoDB, Redis.

• Working with feature stores and model deployment pipelines.

• Experience hiring, mentoring, and doing technical interviews.

• Can explain complex technical concepts to non-technical stakeholders.

• Proactive problem solver who takes end-to-end ownership.

• Works well across Data Science, Analytics, and Engineering teams.

• The role will need to secure a clearance, due to the sensitivity of the project.

To apply:

Please send your latest CV in MS Word format to *************

Appreciate the interest of all applicants; however only shortlisted candidates will be notified.

EA Licence No: 20S0237