Data Engineer
Role Overview
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 . 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. Key Responsibilities 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. Preferred Skills Experience with Snowflake features: Snowpipe Tasks Streams Stages Storage Integrations Stored Procedures Experience migrating Oracle Data Warehouse or legacy platforms to Snowflake. Experience handling semi-structured data (JSON, XML, VARIANT). AWS knowledge, especially: Amazon S3 IAM Encryption Cloud integration Experience with Git, CI/CD, and deployment automation. Exposure to Tableau or other BI reporting tools. Snowflake, AWS, Data Engineering, AI/ML, or GenAI certifications.
Snowflake Data Engineer
to support the modernization of an enterprise data warehouse to a cloud-native analytics platform on
AWS and Snowflake . 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. Key Responsibilities 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. Preferred Skills Experience with Snowflake features: Snowpipe Tasks Streams Stages Storage Integrations Stored Procedures Experience migrating Oracle Data Warehouse or legacy platforms to Snowflake. Experience handling semi-structured data (JSON, XML, VARIANT). AWS knowledge, especially: Amazon S3 IAM Encryption Cloud integration Experience with Git, CI/CD, and deployment automation. Exposure to Tableau or other BI reporting tools. Snowflake, AWS, Data Engineering, AI/ML, or GenAI certifications.