- 经验
- 3+ yrs
- 薪水
- —
- 职位空缺
- 1
- 发布
- 2小时前
- Work mode
- 在办公室
- Eligibility
- Candidates with at least 3 years of relevant end-to-end data warehouse and data management experience are preferred. Freshers from reputed institutions in data science with strong learning ability may also be considered. Experience in logistics or transportation is a plus, and applicants should be…
- Resume
- Required to apply
Where you'll work
职位描述
Position Summary
This position is for a data advocate who will focus on data and machine learning engineering, while also bringing solid data science and analytical capability. The person selected should be comfortable working across the Snowflake and Azure ecosystems, building visual reports in Qlik, and supporting DevOps as well as MLOps workflows. Prior exposure to logistics can be useful, but the key expectation is a strong willingness to learn the domain.
Responsibilities
- Lead the design, build, and upkeep of data and machine learning engineering initiatives.
- Develop and support data and ML pipelines using Snowflake and Azure technologies.
- Design and deliver visual dashboards and reports with Qlik.
- Help ensure models move smoothly from development to deployment through DevOps and MLOps practices.
- Work closely with teams across functions to understand requirements and turn data into practical insights.
- Promote a culture of data-led decision-making throughout the organization.
- Encourage better data understanding and literacy across the business unit.
Requirements
- At least 3 years of hands-on experience delivering end-to-end data warehouse and data management solutions; fresh graduates from reputable institutions with strong learning ability may also be considered.
- Strong practical exposure to the Azure Data platform, Snowflake, SnowPark, MLOps, and DevOps.
- Experience in logistics or transportation, along with familiarity with the related data standards, is preferred.
- Agile, DAMA, or Azure certification will be an added advantage.
- Comfort in working with both technical and non-technical stakeholders, backed by a proactive and constructive approach.
- Strong teamwork mindset, adaptability, and persistence to help drive results.
- Ability to collaborate across teams and translate data needs into useful outcomes.
- Excellent written and verbal communication skills.
Additional Information
This role is based in Singapore and is a full-time onsite position.
The job calls for a candidate who can act as a bridge between data, engineering, and business teams, with a focus on practical delivery and organization-wide data adoption.