Data Integration Engineer – SnapLogic & Snowflake
Summary
Build and maintain data pipelines that ingest and load source data into Snowflake using SnapLogic, enabling analytics and reporting for an Animal Health omnichannel platform.
Rate: max 160 pln/h netto + VAT, B2B
Location: remote
Summary: This role involves designing, building, and maintaining data ingestion pipelines on the Snowflake platform using SnapLogic, focusing on onboarding data sources for enabling analytics and reporting within the Animal Health sector.
Responsibilities:
Design, build, and maintain data ingestion pipelines using SnapLogic.
Integrate data from enterprise applications, REST APIs, databases, cloud storage, and file-based sources.
Load data into Snowflake and ensure data quality, completeness, and reliability.
Implement full and incremental data ingestion processes.
Analyze source data structures and support data discovery activities.
Perform data validation and troubleshoot integration issues.
Monitor and optimize ingestion pipelines.
Support onboarding of new data sources and enhancements to existing integrations.
Create and maintain technical documentation.
Must Haves:
Experience in Data Integration, ETL/ELT, or Data Engineering.
Hands-on experience with SnapLogic.
Experience building data ingestion pipelines into Snowflake.
Strong SQL skills.
Experience integrating REST APIs, relational databases, and file-based data sources.
Good understanding of ETL/ELT concepts and data integration best practices.
Experience with incremental loading and data quality validation.
Strong analytical and problem-solving skills.
Ability to collaborate effectively with both technical and business stakeholders.
Experience working in Agile delivery environments.
Nice to Haves:
Experience with dbt.
Knowledge of Snowflake architecture and cloud data platforms.
Experience with AWS, Azure, or Google Cloud Platform.
Experience working in Life Sciences, Pharma, Animal Health, CRM, Customer Data Platform (CDP), Omnichannel, or Marketing Automation environments.
Familiarity with CI/CD practices and modern data engineering practices.
Other Details:
Work Environment: Agile delivery environments.
Project Context: Part of the Animal Health Omnichannel & Marketing Automation data platform initiative.