Data Engineer (Short-Term Engagement)
Serverless Guru LLC., Wilmington, DE, United States
We are looking for 5+ years of overall data engineering experience, with expert-level hands‑on experience in CData, Snowflake, and Looker schema development. As a senior data engineer, you will bring best practices for modern data architecture, data modeling, and analytics enablement, helping ensure that data pipelines and reporting layers are performant, scalable, and easy for business users to consume. Your expertise in data integration and modeling will be critical to the success of this short‑term engagement and will directly impact the client’s ability to make data‑driven decisions.
About the Role
As a Data Engineer, you will work closely with technical and business teams to build and optimize data pipelines and analytics layers. You will be responsible for integrating multiple data sources using CData, transforming and modeling data within Snowflake, and creating structured, scalable Looker schemas to support reporting and insights.
Key Responsibilities
Design, build, and optimize data pipelines using CData connectors
Ingest and transform data into Snowflake for analytics and reporting
Develop and maintain scalable data models within Snowflake
Build and optimize Looker schemas (LookML) for business intelligence use cases
Ensure data quality, consistency, and reliability across systems
Collaborate with stakeholders to understand reporting requirements and translate them into technical solutions
Troubleshoot and resolve data pipeline and modeling issues
Implement best practices for data governance, performance optimization, and scalability
Required Skills & Experience
5+ years of overall data engineering experience
Expert‑level experience with CData (connectors, integrations, and data ingestion)
Strong expertise in Snowflake (data modeling, performance tuning, ETL/ELT)
Extensive experience building Looker schemas (LookML)
Strong SQL skills and experience working with large datasets
Experience designing and implementing end‑to‑end data pipelines
Familiarity with data integration patterns and best practices
Experience working in Agile development environments
Strong problem‑solving and communication skills
Preferred Qualifications
Experience with BI tools beyond Looker
Familiarity with modern data stack tools
Experience with data governance and data quality frameworks
Exposure to cloud‑based data ecosystems
Experience with manufacturing or distribution data (nice to have)
Engagement Details
Duration: 4-5 weeks (40 hrs/week)
Timezone: EST
Client industry: manufacturing and distribution (related industry experience not required; the role is fully on the data side)
Join our team and help deliver a high‑impact data solution that enables smarter decision‑making and scalable analytics for our client.
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About the Role
As a Data Engineer, you will work closely with technical and business teams to build and optimize data pipelines and analytics layers. You will be responsible for integrating multiple data sources using CData, transforming and modeling data within Snowflake, and creating structured, scalable Looker schemas to support reporting and insights.
Key Responsibilities
Design, build, and optimize data pipelines using CData connectors
Ingest and transform data into Snowflake for analytics and reporting
Develop and maintain scalable data models within Snowflake
Build and optimize Looker schemas (LookML) for business intelligence use cases
Ensure data quality, consistency, and reliability across systems
Collaborate with stakeholders to understand reporting requirements and translate them into technical solutions
Troubleshoot and resolve data pipeline and modeling issues
Implement best practices for data governance, performance optimization, and scalability
Required Skills & Experience
5+ years of overall data engineering experience
Expert‑level experience with CData (connectors, integrations, and data ingestion)
Strong expertise in Snowflake (data modeling, performance tuning, ETL/ELT)
Extensive experience building Looker schemas (LookML)
Strong SQL skills and experience working with large datasets
Experience designing and implementing end‑to‑end data pipelines
Familiarity with data integration patterns and best practices
Experience working in Agile development environments
Strong problem‑solving and communication skills
Preferred Qualifications
Experience with BI tools beyond Looker
Familiarity with modern data stack tools
Experience with data governance and data quality frameworks
Exposure to cloud‑based data ecosystems
Experience with manufacturing or distribution data (nice to have)
Engagement Details
Duration: 4-5 weeks (40 hrs/week)
Timezone: EST
Client industry: manufacturing and distribution (related industry experience not required; the role is fully on the data side)
Join our team and help deliver a high‑impact data solution that enables smarter decision‑making and scalable analytics for our client.
#J-18808-Ljbffr