Data Engineer/ Analytics Engineer (JD#11356)

Sciente International Pte Ltd; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Sciente International Pte Ltd is seeking a mid-level Analytics Engineer / Data Engineer to build and modernize data pipelines and analytics platforms for a leading bank. You will craft reliable data flows, analytical models, and reusable logic using modern cloud technologies.

The role requires 3–6 years of data engineering exposure, strong SQL and Python, plus experience with dbt and orchestration tools such as Airflow or Cloud Composer.

Qualifications

• Degree in Computer Science, Data Analytics, Information Technology or related field.
• 3–6 years of experience in Data Engineering, Analytics Engineering, Data Warehousing, or related areas.
• Strong hands-on experience with SQL.
• Proficient Python for data processing and automation.
• Strong dimensional data modelling knowledge (Star schemas, Fact/Dimension tables, Data marts).
• Hands-on experience with dbt or equivalent data transformation framework.
• Experience with workflow orchestration tools such as Airflow or Cloud Composer.
• Solid understanding of ETL/ELT concepts and data warehousing.
• Knowledge of semantic layers, business metrics, and reusable business logic.
• Familiarity with Git/version control, code reviews, testing, CI/CD.
• Ability to troubleshoot data quality and pipeline issues independently.

Responsibilities

• Design, develop, and maintain data pipelines and analytic datasets.
• Develop and optimize SQL-based transformations and data models.
• Build and maintain dimensional data models (fact/dimension tables, star schemas, data marts).
• Develop data transformation workflows using dbt or equivalent frameworks.
• Manage workflows with Airflow, Cloud Composer, or equivalent tools.
• Implement reusable business logic and common metrics.
• Support development of semantic and analytical layers.
• Implement data quality checks, testing, validation, and monitoring.
• Investigate and resolve data, pipeline, and transformation issues.
• Identify root causes and apply corrective actions.
• Follow software engineering best practices (Git, reviews, testing, CI/CD).
• Collaborate with Data Engineers, Analytics Engineers, Developers, Analysts, and Business Stakeholders.
• Understand and migrate legacy/.NET processes as needed.
• Advocate modern cloud-based data engineering and analytics practices.
• Ensure data solutions are reliable, scalable, maintainable, and reusable.
• Support BI and reporting with trusted datasets.

Skills

SQL

Python

Dimensional modelling

dbt

Airflow

ETL/ELT

Data warehousing

Git/CI-CD

Data quality

Data modeling

Education

Degree in CS/IT/Data Analytics

Tools

GCP

dbt

Apache Airflow

Cloud Composer

Job description

Job Summary

We are looking for a mid-level Analytics Engineer / Data Engineer with 3–6 years of relevant experience to support the development, modernization, and maintenance of data and analytics platform for a reputed bank .The role will involve building reliable data pipelines, developing analytical data models, implementing reusable business logic, troubleshooting data issues, and contributing to the modernization of existing data processes using modern software engineering and cloud technologies.

Mandatory Skill-set

• Degree in Computer Science, Data Analytics, Information Technology and related discipline;
• 3–6 years of experience in Data Engineering, Analytics Engineering, Data Warehousing, or related areas;
• Strong hands-on experience with SQ;
• Good working knowledge of Python for data processing and automation;
• Strong understanding of dimensional data modelling, including: Star schemas, Fact tables, Dimension tables, Data marts,Star schemas, Fact tables, Dimension tables, Data marts;
• Hands-on experience with dbt or an equivalent data transformation framework;
• Experience with at least one workflow orchestration tool, such as: Apache Airflow,Cloud Composer, Equivalent orchestration platforms;
• Good understanding of ETL/ELT concepts and data warehousing;
• Understanding of semantic layers, business metrics, and reusable business logic;
• Knowledge of software engineering best practices, including: Git/version control, Code reviews, Unit and data testing, CI/CD;
• Ability to troubleshoot data quality, pipeline, and transformation issues independently.

Desired Skill-set

• Experience working with Google Cloud Platform (GCP);
• Experience with cloud data platforms and cloud-native data engineering solutions.

Responsibilities

• Design, develop, and maintain data pipelines and analytical datasets;
• Develop and optimize SQL-based transformations and data models;
• Build and maintain dimensional data models, including fact tables, dimension tables, star schemas, and data marts;
• Develop data transformation workflows using dbt or equivalent frameworks;
• Develop and manage workflows using Airflow, Cloud Composer, or equivalent orchestration tools;
• Implement reusable business logic and common business metrics;
• Support the development and maintenance of semantic and analytical layers;
• Implement data quality checks, testing, validation, and monitoring;
• Investigate and resolve data, pipeline, and transformation issues;
• Identify root causes of data issues and implement appropriate corrective actions;
• Follow software engineering best practices, including Git, code reviews, testing, documentation, and CI/CD;
• Work closely with Data Engineers, Analytics Engineers, Developers, Analysts, and Business Stakeholders;
• Understand existing legacy/.NET business processes and support their migration, redesign, or modernization;
• Contribute to the adoption of modern cloud-based data engineering and analytics practices;
• Ensure data solutions are reliable, scalable, maintainable, and reusable;
• Support BI and reporting requirements by providing trusted and well-structured analytical datasets.

EA Licence No. 07C5639