Data Engineer (Azure) (4-7 Years Experience) (SG Citizen/PR) (1 Year Contract)
Posted
Rhino Partners Pte Ltd Data Engineer (Azure) (4-7 Years Experience) (SG Citizen/PR) (1 Year Contract)
Summary
A 1-year contract data engineering role in Singapore (citizens/PRs only) focused on designing, building, and optimizing scalable data pipelines and ETL/ELT workflows on Azure (Synapse, Data Factory) using Python and SQL. The role also involves business analysis, requirements gathering, and stakeholder engagement.
We are looking for an experienced Data Engineer with strong hands-on engineering capabilities and the ability to work closely with business stakeholders to translate requirements into practical data solutions.
In this role, you will design, build, and optimise scalable data pipelines and data processing workflows across cloud-based platforms. You will also play an important role in understanding business requirements, documenting processes, and ensuring that technical solutions effectively support analytics, reporting, and broader business needs.
This role is well suited to someone who combines strong data engineering expertise in Azure, Python, and SQL with good stakeholder engagement and business analysis capabilities.
ResponsibilitiesData Engineering & Pipeline Development
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows across cloud-based data platforms. Build and optimise data processing and transformation workflows using Python and SQL. Develop and maintain data models to support analytics, reporting, and downstream data consumption. Monitor data pipelines and storage solutions, troubleshoot issues, and continuously improve reliability and performance. Ensure data solutions are scalable, maintainable, and aligned with established engineering practices.
Azure Data Platform
Develop and maintain data solutions using Azure Synapse Analytics and Azure Data Factory (ADF). Build and manage data ingestion, transformation, orchestration, and integration workflows within the Azure ecosystem. Support the optimisation of cloud-based data processing and storage solutions.
Business Analysis & Stakeholder Engagement
Work closely with business and technical stakeholders to understand requirements, processes, and data needs. Translate business requirements into clear technical specifications and data solutions. Document business requirements, workflows, processes, and solution requirements. Facilitate discussions between technical and non-technical stakeholders to ensure alignment on requirements and expected outcomes. Identify opportunities to improve existing data processes and workflows. Analytics & Cross-Functional Collaboration
Collaborate with analytics, reporting, and business teams to ensure data is appropriately structured and available for downstream consumption. Support integration with reporting and analytics platforms where required. Work collaboratively with engineers, analysts, and other stakeholders throughout the delivery lifecycle.
Requirements
5–7 years of experience in Data Engineering or a related role. Strong hands-on experience with Azure Synapse Analytics and Azure Data Factory (ADF). Strong proficiency in Python and SQL for data processing, transformation, and pipeline development. Experience designing and implementing ETL/ELT pipelines, data transformations, and data models. Demonstrated business analysis experience, including requirements gathering, stakeholder engagement, and process documentation. Ability to translate business requirements into practical technical solutions. Strong analytical and problem-solving skills. Strong written and verbal communication skills, with the ability to engage effectively with both technical and non-technical stakeholders.
Good to Have
Experience with Databricks and/or Snowflake. Experience with Power BI or other analytics and visualisation platforms. Broader experience working within cloud data ecosystems, particularly Microsoft Azure.
This role is well suited to someone who combines strong data engineering expertise in Azure, Python, and SQL with good stakeholder engagement and business analysis capabilities.
ResponsibilitiesData Engineering & Pipeline Development
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows across cloud-based data platforms. Build and optimise data processing and transformation workflows using Python and SQL. Develop and maintain data models to support analytics, reporting, and downstream data consumption. Monitor data pipelines and storage solutions, troubleshoot issues, and continuously improve reliability and performance. Ensure data solutions are scalable, maintainable, and aligned with established engineering practices.
Azure Data Platform
Develop and maintain data solutions using Azure Synapse Analytics and Azure Data Factory (ADF). Build and manage data ingestion, transformation, orchestration, and integration workflows within the Azure ecosystem. Support the optimisation of cloud-based data processing and storage solutions.
Business Analysis & Stakeholder Engagement
Work closely with business and technical stakeholders to understand requirements, processes, and data needs. Translate business requirements into clear technical specifications and data solutions. Document business requirements, workflows, processes, and solution requirements. Facilitate discussions between technical and non-technical stakeholders to ensure alignment on requirements and expected outcomes. Identify opportunities to improve existing data processes and workflows. Analytics & Cross-Functional Collaboration
Collaborate with analytics, reporting, and business teams to ensure data is appropriately structured and available for downstream consumption. Support integration with reporting and analytics platforms where required. Work collaboratively with engineers, analysts, and other stakeholders throughout the delivery lifecycle.
Requirements
5–7 years of experience in Data Engineering or a related role. Strong hands-on experience with Azure Synapse Analytics and Azure Data Factory (ADF). Strong proficiency in Python and SQL for data processing, transformation, and pipeline development. Experience designing and implementing ETL/ELT pipelines, data transformations, and data models. Demonstrated business analysis experience, including requirements gathering, stakeholder engagement, and process documentation. Ability to translate business requirements into practical technical solutions. Strong analytical and problem-solving skills. Strong written and verbal communication skills, with the ability to engage effectively with both technical and non-technical stakeholders.
Good to Have
Experience with Databricks and/or Snowflake. Experience with Power BI or other analytics and visualisation platforms. Broader experience working within cloud data ecosystems, particularly Microsoft Azure.