Job description

Marlabs, a global AI and Digital Solutions Consulting firm, delivers intelligent solutions across AI, data, analytics, and product engineering. Since 2000, we have partnered with some of the largest healthcare, life sciences, financial services, and government organizations worldwide. As we continue to expand our global footprint, we have an exciting opportunity for a highly skilled Data Engineer (Snowflake & dbt) to join our innovative and dynamic team. Data Engineer (Snowflake & dbt) | About the Role As a Data Engineer (Snowflake & dbt), you will be responsible for designing, developing, and optimizing modern cloud-based data solutions that enable scalable analytics, reporting, and business intelligence capabilities. You will leverage your expertise in Snowflake, dbt, SQL, Python, and Azure DevOps to build high-performance data pipelines, develop robust data models, and support enterprise data platforms. The ideal candidate combines strong data engineering fundamentals with hands-on experience in Snowflake architecture, data transformation, CI/CD automation, and modern data warehousing best practices. Data Engineer (Snowflake & dbt) | Day-to-Day • Design, develop, and maintain scalable ETL/ELT pipelines and data integration solutions using Snowflake, dbt, SQL, and Python. • Build and optimize complex data transformation workflows, ensuring high-performance data processing, data quality, and reliability across the data platform. • Develop and maintain Snowflake data models, including OLTP, OLAP, and Data Vault 2.0 methodologies to support enterprise analytics and reporting requirements. • Create, manage, and optimize dbt models, macros, tests, and transformation frameworks to support governed and reusable data assets. • Design, implement, and maintain CI/CD pipelines using Azure DevOps, Git, and deployment automation tools to support efficient release management and code promotion processes. • Collaborate with data architects, analysts, and business stakeholders to design scalable data solutions and support evolving business requirements. • Perform performance tuning, query optimization, and troubleshooting to improve Snowflake workload efficiency, scalability, and data processing performance. • Document data models, transformation logic, workflows, and operational procedures while supporting governance, compliance, and knowledge-sharing initiatives. Data Engineer (Snowflake & dbt) | Skills & Experience • 5+ years of experience in Data Engineering, including hands-on experience building enterprise data pipelines, ETL/ELT frameworks, and cloud-based data solutions. • Strong expertise in Snowflake, SQL, and Python, including advanced query development, data transformation, performance tuning, and large-scale data processing. • Proven experience with dbt (Data Build Tool), including developing and maintaining dbt models, macros, testing frameworks, and transformation workflows. • Experience implementing CI/CD pipelines and version control practices, using Azure DevOps, Git repositories, deployment automation, and release management processes. • Strong understanding of data modeling and warehousing concepts, including OLTP, OLAP, Data Vault 2.0, dimensional modeling, and enterprise data architecture. • Preferred: Experience with Azure, AWS, data governance, data security, compliance requirements, and mentoring junior developers or supporting technical leadership activities.

Requirements

Must-haves

Data Engineer (Snowflake & dbt) | About the Role
Data Engineer (Snowflake & dbt) | Day-to-Day
Design, develop, and maintain scalable ETL/ELT pipelines and data integration solutions using Snowflake, dbt, SQL, and Python.
Build and optimize complex data transformation workflows, ensuring high-performance data processing, data quality, and reliability across the data platform.
Develop and maintain Snowflake data models, including OLTP, OLAP, and Data Vault 2.0 methodologies to support enterprise analytics and reporting requirements.
Create, manage, and optimize dbt models, macros, tests, and transformation frameworks to support governed and reusable data assets.
Design, implement, and maintain CI/CD pipelines using Azure DevOps, Git, and deployment automation tools to support efficient release management and code promotion processes.
Collaborate with data architects, analysts, and business stakeholders to design scalable data solutions and support evolving business requirements.
Perform performance tuning, query optimization, and troubleshooting to improve Snowflake workload efficiency, scalability, and data processing performance.
Document data models, transformation logic, workflows, and operational procedures while supporting governance, compliance, and knowledge-sharing initiatives.
Data Engineer (Snowflake & dbt) | Skills & Experience
5+ years of experience in Data Engineering, including hands-on experience building enterprise data pipelines, ETL/ELT frameworks, and cloud-based data solutions.
Strong expertise in Snowflake, SQL, and Python, including advanced query development, data transformation, performance tuning, and large-scale data processing.
Proven experience with dbt (Data Build Tool), including developing and maintaining dbt models, macros, testing frameworks, and transformation workflows.
Experience implementing CI/CD pipelines and version control practices, using Azure DevOps, Git repositories, deployment automation, and release management processes.
Strong understanding of data modeling and warehousing concepts, including OLTP, OLAP, Data Vault 2.0, dimensional modeling, and enterprise data architecture.

Nice-to-haves

Preferred: Experience with Azure, AWS, data governance, data security, compliance requirements, and mentoring junior developers or supporting technical leadership activities.

Application prep

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Platform: breezy
Effort: medium