Data Engineering Lead (Snowflake) (1 Year Contract)
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Summary
Leads the design and delivery of scalable data pipelines and data products on Snowflake for a one-year contract in Singapore. Day to day: building ETL/ELT with SQL, Python and Snowpark (Dynamic Tables, Streams, Tasks, Snowpipe), enforcing engineering standards, handling governance/CI/CD, and mentoring Data Engineers.
We are looking for an experienced
Data Engineering Lead
to lead the design, development, and delivery of scalable data pipelines and data solutions on Snowflake.
In this role, you will be responsible for translating data architecture into production-ready solutions, establishing engineering best practices, and guiding a team of Data Engineers. You will work closely with Solution Architects, business stakeholders, and technical teams to deliver secure, reliable, and high-performing data platforms that support analytics, reporting, and business applications.
Responsibilities
Data Engineering & Development Lead the design, development, and implementation of scalable data pipelines, data models, and data products using Snowflake. Build and optimise ETL/ELT pipelines for data ingestion, transformation, integration, and processing. Implement data processing across Bronze, Silver, Gold, and Platinum data layers. Develop solutions using SQL, Python, and Snowflake capabilities such as Dynamic Tables, Streams, Tasks, Snowpipe, and Snowpark. Design and maintain data marts and structured datasets to support analytics and reporting requirements.
Technical Leadership & Engineering Standards Provide technical leadership and guidance to Data Engineers throughout the development lifecycle. Establish and enforce engineering standards for coding, data modelling, testing, documentation, and deployment. Conduct technical reviews, troubleshoot complex engineering issues, and address delivery risks. Collaborate with Solution Architects to translate architectural designs into practical engineering solutions. Work with stakeholders to understand business requirements and translate them into technical specifications and deliverables.
Data Quality, Security & Governance Implement data quality checks, validation, reconciliation, lineage, and monitoring processes. Work with architecture and security teams to implement role-based access control (RBAC), data classification, masking policies, and secure data sharing. Ensure data pipelines and solutions meet security, governance, reliability, and performance requirements.
Deployment & Platform Operations Manage CI/CD processes and deployment of Snowflake objects and data pipelines across Development, UAT, and Production environments. Monitor and optimise pipeline performance, data processing efficiency, and platform reliability. Investigate and resolve pipeline failures, data quality issues, access-related issues, and performance bottlenecks. Develop technical documentation, operational runbooks, and knowledge-transfer materials to support ongoing platform operations.
Requirements
At least 6 years of experience in Data Engineering, including a minimum of 1 year of hands-on Snowflake experience. Strong proficiency in SQL and Python, with experience in Snowpark Python where applicable. Hands-on experience designing, developing, and optimising ETL/ELT pipelines, data models, and data marts. Experience with Snowflake capabilities such as Dynamic Tables, Streams, Tasks, Snowpipe, stages, and secure data sharing. Strong understanding of data quality, testing, monitoring, reconciliation, and troubleshooting. Experience with Git-based version control, CI/CD pipelines, and automated deployment processes. Demonstrated experience leading technical delivery, conducting code reviews, and mentoring Data Engineers. Strong problem-solving and communication skills, with the ability to collaborate across technical teams and business stakeholders.
Good to Have
Experience with Azure Data Factory (ADF), Azure Blob Storage, and Power BI. Experience implementing Snowflake security and governance features, including RBAC, masking policies, tagging, and data classification. Snowflake certification.
Data Engineering Lead
to lead the design, development, and delivery of scalable data pipelines and data solutions on Snowflake.
In this role, you will be responsible for translating data architecture into production-ready solutions, establishing engineering best practices, and guiding a team of Data Engineers. You will work closely with Solution Architects, business stakeholders, and technical teams to deliver secure, reliable, and high-performing data platforms that support analytics, reporting, and business applications.
Responsibilities
Data Engineering & Development Lead the design, development, and implementation of scalable data pipelines, data models, and data products using Snowflake. Build and optimise ETL/ELT pipelines for data ingestion, transformation, integration, and processing. Implement data processing across Bronze, Silver, Gold, and Platinum data layers. Develop solutions using SQL, Python, and Snowflake capabilities such as Dynamic Tables, Streams, Tasks, Snowpipe, and Snowpark. Design and maintain data marts and structured datasets to support analytics and reporting requirements.
Technical Leadership & Engineering Standards Provide technical leadership and guidance to Data Engineers throughout the development lifecycle. Establish and enforce engineering standards for coding, data modelling, testing, documentation, and deployment. Conduct technical reviews, troubleshoot complex engineering issues, and address delivery risks. Collaborate with Solution Architects to translate architectural designs into practical engineering solutions. Work with stakeholders to understand business requirements and translate them into technical specifications and deliverables.
Data Quality, Security & Governance Implement data quality checks, validation, reconciliation, lineage, and monitoring processes. Work with architecture and security teams to implement role-based access control (RBAC), data classification, masking policies, and secure data sharing. Ensure data pipelines and solutions meet security, governance, reliability, and performance requirements.
Deployment & Platform Operations Manage CI/CD processes and deployment of Snowflake objects and data pipelines across Development, UAT, and Production environments. Monitor and optimise pipeline performance, data processing efficiency, and platform reliability. Investigate and resolve pipeline failures, data quality issues, access-related issues, and performance bottlenecks. Develop technical documentation, operational runbooks, and knowledge-transfer materials to support ongoing platform operations.
Requirements
At least 6 years of experience in Data Engineering, including a minimum of 1 year of hands-on Snowflake experience. Strong proficiency in SQL and Python, with experience in Snowpark Python where applicable. Hands-on experience designing, developing, and optimising ETL/ELT pipelines, data models, and data marts. Experience with Snowflake capabilities such as Dynamic Tables, Streams, Tasks, Snowpipe, stages, and secure data sharing. Strong understanding of data quality, testing, monitoring, reconciliation, and troubleshooting. Experience with Git-based version control, CI/CD pipelines, and automated deployment processes. Demonstrated experience leading technical delivery, conducting code reviews, and mentoring Data Engineers. Strong problem-solving and communication skills, with the ability to collaborate across technical teams and business stakeholders.
Good to Have
Experience with Azure Data Factory (ADF), Azure Blob Storage, and Power BI. Experience implementing Snowflake security and governance features, including RBAC, masking policies, tagging, and data classification. Snowflake certification.