DATA ENGINEER

ELLIOTT MOSS CONSULTING PTE. LTD.; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Elliott Moss Consulting PTE. LTD. is seeking a hands-on Snowflake Data Engineer to help modernize an enterprise data warehouse into a cloud-native analytics platform on AWS and Snowflake.

You will design scalable data pipelines, build dimensional models, implement ELT/ETL workflows, and optimize SQL while collaborating with architects, QA, cloud engineers, and business stakeholders in an Agile environment. The role requires 3+ years in data engineering and strong Snowflake/AWS experience, with

Qualifications

• 3+ years of experience in Data Engineering, Data Warehousing, or Database Development.
• Hands-on experience with Snowflake or another cloud data warehouse platform.
• Strong SQL skills including joins, window functions, CTEs, query optimization, and troubleshooting.
• Good understanding of dimensional modelling (Star Schema, Fact & Dimension tables).
• Experience developing and maintaining ETL/ELT pipelines.
• Knowledge of data quality, reconciliation, logging, monitoring, and production support.

Responsibilities

• Build scalable data pipelines, develop dimensional data models, and deliver reliable ELT solutions with architects, senior engineers, QA teams, cloud engineers, and business stakeholders.
• Design, develop, and maintain data pipelines and warehouse layers (RAW, ODS, DW) in Snowflake.
• Build and support ELT/ETL pipelines using Snowflake features such as Snowpipe, Tasks, Streams, Stages, Storage Integrations, and Stored Procedures.
• Develop dimensional data models including fact tables, dimension tables, aggregates, and lookup tables.
• Write, optimize, and troubleshoot complex SQL queries for transformation, reconciliation, and performance tuning.
• Implement data quality checks, validation, reconciliation, logging, and error-handling mechanisms.
• Support rerun, recovery, and replay processes for failed data loads.
• Integrate data securely using AWS services such as S3 and IAM.
• Participate in SIT, UAT, deployment, documentation, and production support.
• Collaborate with architects and engineering teams while following coding standards and best practices.
• Contribute to code reviews and continuous improvement initiatives.

Skills

Snowflake/Data Warehouse

SQL proficiency

Dimensional modelling

ETL/ELT pipelines

Problem solving

Communication

Tools

Snowflake

AWS

ETL tools

Job description

Job Description

We are looking for a hands-on Snowflake Data Engineer to support the modernization of an enterprise data warehouse to a cloud-native analytics platform on AWS and Snowflake.

Key Responsibilities

• You will be responsible for building scalable data pipelines, developing dimensional data models, and delivering reliable ELT solutions while working closely with architects, senior engineers, QA teams, cloud engineers, and business stakeholders.
• Design, develop, and maintain data pipelines and warehouse layers (RAW, ODS, DW) in Snowflake.
• Build and support ELT/ETL pipelines using Snowflake features such as Snowpipe, Tasks, Streams, Stages, Storage Integrations, and Stored Procedures.
• Develop dimensional data models including fact tables, dimension tables, aggregates, and lookup tables.
• Write, optimize, and troubleshoot complex SQL queries for transformation, reconciliation, and performance tuning.
• Implement data quality checks, validation, reconciliation, logging, and error-handling mechanisms.
• Support rerun, recovery, and replay processes for failed data loads.
• Integrate data securely using AWS services such as S3 and IAM.
• Participate in SIT, UAT, deployment, documentation, and production support.
• Collaborate with architects and engineering teams while following coding standards and best practices.
• Contribute to code reviews and continuous improvement initiatives.

Required Skills & Experience

• 3+ years of experience in Data Engineering, Data Warehousing, or Database Development.
• Hands-on experience with Snowflake or another cloud data warehouse platform.
• Strong SQL skills including joins, window functions, CTEs, query optimization, and troubleshooting.
• Good understanding of dimensional modelling (Star Schema, Fact & Dimension tables).
• Experience developing and maintaining ETL/ELT pipelines.
• Knowledge of data quality, reconciliation, logging, monitoring, and production support.
• Good analytical, communication, and problem-solving skills.
• Ability to work independently and collaboratively in an Agile delivery environment.