Data Engineer

ENFACTUM PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading data services company in Singapore is seeking an experienced data specialist to manage datasets and data pipelines, support ad-hoc business needs, and resolve data-related issues. Candidates should have hands-on Big Data experience using technologies like Hadoop and Spark, along with expert SQL skills. The position involves collaborating with various stakeholders to advance the data strategy and promoting effective data processes. Familiarity with data science tools and processes is a plus.

Qualifications

• Hands-on Big Data experience using common open-source components.
• Experience in stakeholder management in heterogeneous business/technology organizations.
• Experience in large data migration projects with on-prem Data Lakes.

Responsibilities

• Prepare datasets and data pipelines while troubleshooting data issues.
• Collaborate to co-design Enterprise Data Strategy.
• Maintain and model JSON-based schemas for organization-wide reuse.

Skills

Big Data experience using common open-source components

Expert SQL skills

Automation experience in Python

Data preparation for reporting/analytics

Knowledge of reference architectures

Good knowledge of German

Tools

Hadoop

Spark

Dataiku

Tableau

Job description

Role description

• Datasets and data pipelines preparation, support for Business, data troubleshooting.
• Closely collaborate with the Data & Analytics Program Management and stakeholders to co-design Enterprise Data Strategy and Common Data Model
• Implementation and promotion of Data Platform, transformative data processes, and services
• Develop data pipelines and structures for Data Scientists, testing such to ensure that they are fit for use
• Maintain and model JSON based schemas and metadata to re-use it across the organization (with central tools)
• Resolving and troubleshooting data related issues and queries
• Covering all processes from enterprise reporting to data science (incl. ML Ops)

Experience

• Hands‑on Big Data experience using common open‑source components (Hadoop, Hive, Spark, Presto, NiFi, MinIO, KBS, Kafka)
• Experience in stakeholder management in heterogeneous business / technology organizations
• Experience in banking or financial business, with handling sensitive data across regions
• Experience in large data migration projects with on‑prem Data Lakes
• Hands‑on experience in integrating Data Science Workbench platforms (e.g., Knime, Cloudera, Dataiku)
• Track record in Agile project management and methods (e.g., Scrum, SAFe).

Skills

• Knowledge of reference architectures, especially concerning integrated, data‑driven landscapes and solutions
• Expert SQL skills, preferably in mixed environments (i.e. classic DWH and distributed)
• Working automation and troubleshooting experience in Python using Jupyter Notebooks or common IDEs
• Data preparation for reporting / analytics and visualization tools (e.g. Tableau, Power BI or Python based)
• Applying a data quality framework within the architecture
• Good knowledge of German is beneficial, excellent command of English is essential