DATA ENGINEER

AXIOM RISE CONSULTANCY PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

AXIOM RISE CONSULTANCY PTE. LTD. in Singapore seeks a senior Data Engineer to design, build, and optimize scalable data pipelines and cloud-based data platforms.

You will develop robust SQL and Python transformations, implement data quality frameworks, and collaborate with cross-functional teams to deliver reliable data solutions for analytics and reporting. The role requires strong experience in data warehousing, modern data lake architectures, and cloud services (AWS/Azure/GCP), along with

Qualifications

• 10+ years of IT experience with at least 5 years of hands-on Data Engineering experience.
• Strong proficiency in SQL and Python.
• Hands-on experience with ETL/ELT development and data pipeline orchestration.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with technologies such as Databricks, Apache Spark/PySpark, Amazon Redshift, AWS Glue, Amazon S3, or equivalent cloud data services.
• Strong understanding of data warehousing, dimensional modeling, and modern data lake architectures.
• Experience working with relational databases, APIs, file-based integrations, and cloud storage.
• Knowledge of data quality, metadata management, and data governance principles.
• Experience working in Agile/Scrum environments.
• Excellent analytical, problem-solving, and stakeholder communication skills.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines to ingest, transform, and integrate data from multiple source systems.
• Build and maintain cloud-based data platforms, data lakes, and data warehouses to support analytics and reporting.
• Develop robust SQL and Python-based data transformation logic, ensuring high performance and scalability.
• Implement data validation, reconciliation, monitoring, and quality frameworks to ensure data accuracy and reliability.
• Collaborate with business, product, analytics, and engineering teams to gather requirements and deliver data solutions aligned with business objectives.
• Develop and optimize data models, staging layers, and curated datasets for BI reporting and downstream applications.
• Integrate data from APIs, databases, cloud storage, and third-party systems using modern integration techniques.
• Troubleshoot data pipeline issues, optimize performance, and support production deployments.
• Implement data governance, security, documentation, and best practices throughout the data lifecycle.
• Participate in Agile ceremonies, code reviews, and continuous improvement initiatives.

Skills

SQL

Python

Data modeling

Agile/Scrum

Analytical thinking

Stakeholder communication

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field

Tools

Databricks

Apache Spark

Amazon Redshift

AWS Glue

Amazon S3

Airflow

CI/CD

Git

Power BI

Tableau

Job description

Key Responsibilities

• Design, develop, and optimize scalable ETL/ELT pipelines to ingest, transform, and integrate data from multiple source systems.
• Build and maintain cloud-based data platforms, data lakes, and data warehouses to support analytics and reporting.
• Develop robust SQL and Python-based data transformation logic, ensuring high performance and scalability.
• Implement data validation, reconciliation, monitoring, and quality frameworks to ensure data accuracy and reliability.
• Collaborate with business, product, analytics, and engineering teams to gather requirements and deliver data solutions aligned with business objectives.
• Develop and optimize data models, staging layers, and curated datasets for BI reporting and downstream applications.
• Integrate data from APIs, databases, cloud storage, and third-party systems using modern integration techniques.
• Troubleshoot data pipeline issues, optimize performance, and support production deployments.
• Implement data governance, security, documentation, and best practices throughout the data lifecycle.
• Participate in Agile ceremonies, code reviews, and continuous improvement initiatives.

Required Skills & Qualifications

• 10+ years of IT experience with at least 5 years of hands-on Data Engineering experience.
• Strong proficiency in SQL and Python.
• Hands-on experience with ETL/ELT development and data pipeline orchestration.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with technologies such as Databricks, Apache Spark/PySpark, Amazon Redshift, AWS Glue, Amazon S3, or equivalent cloud data services.
• Strong understanding of data warehousing, dimensional modeling, and modern data lake architectures.
• Experience working with relational databases, APIs, file-based integrations, and cloud storage.
• Knowledge of data quality, metadata management, and data governance principles.
• Experience working in Agile/Scrum environments.
• Excellent analytical, problem-solving, and stakeholder communication skills.

Preferred Qualifications

• Experience with workflow orchestration tools such as Apache Airflow or equivalent.
• Experience with CI/CD pipelines, Git, and DevOps practices for data engineering.
• Familiarity with Power BI, Tableau, or other BI tools.
• Cloud certifications (AWS, Azure, Databricks) are a plus.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.