Note: The job is a remote job and is open to candidates in USA. Cimpress invests in and helps build customer-focused, entrepreneurial mass customization businesses, including BuildASign, a provider of personalized wall décor, signage, and large-format products. Cimpress is seeking a Senior Data Engineer to build and manage scalable batch and near-real-time data pipelines, data warehouses, and cloud-based data solutions. The role also focuses on data modeling, machine learning and MLOps practices, and applying AI and generative AI tools to improve engineering productivity.
Responsibilities
- 3+ years of experience handling large data volumes and orchestrating and monitoring automated Batch & Near Real-Time ETL/data pipelines using CI/CD and Cloud Technologies, with preferred expertise in DBT or DBT Cloud
- Strong programming skills in Python and SQL
- Solid experience with MPP Data Warehouse systems such as Snowflake or Amazon Redshift, along with cloud platforms including AWS (Preferred), Azure, or GCP
- Expertise in Data Modelling and Data Warehousing best practices, with a strong ability to adopt development best practices such as modularization, testing, and refactoring
- Experience with Business Intelligence and reporting tools such as Looker is an added advantage
- Hands-on experience with Machine Learning (ML) and MLOps practices, including model training, versioning, deployment, monitoring, and lifecycle management using tools like MLflow, SageMaker, or Vertex AI
- Ability to leverage AI tools in day-to-day data engineering tasks, such as using GitHub Copilot or Claude for code generation, debugging, query optimization, and pipeline development to improve productivity and efficiency
- Exposure to Generative AI tools and frameworks (e.g., LangGraph, LangChain, OpenAI APIs)
- Curiosity to explore and implement evolving data engineering and Generative AI technologies
- Understanding of modern practices like DataOps, MLOps or equivalent experience
- Strong problem-solving skills with a solid understanding of data structures, algorithms, and the ability to thrive in ambiguous environments with minimal oversight
Skills
- Strong programming skills in Python and SQL
- Solid experience with MPP Data Warehouse systems such as Snowflake or Amazon Redshift, along with cloud platforms including AWS (Preferred), Azure, or GCP
- Expertise in Data Modelling and Data Warehousing best practices, with a strong ability to adopt development best practices such as modularization, testing, and refactoring
- Experience with Business Intelligence and reporting tools such as Looker is an added advantage
- Hands-on experience with Machine Learning (ML) and MLOps practices, including model training, versioning, deployment, monitoring, and lifecycle management using tools like MLflow, SageMaker, or Vertex AI
- Ability to leverage AI tools in day-to-day data engineering tasks, such as using GitHub Copilot or Claude for code generation, debugging, query optimization, and pipeline development to improve productivity and efficiency
- Exposure to Generative AI tools and frameworks (e.g., LangGraph, LangChain, OpenAI APIs)
- Curiosity to explore and implement evolving data engineering and Generative AI technologies
- Understanding of modern practices like DataOps, MLOps or equivalent experience
- Strong problem-solving skills with a solid understanding of data structures, algorithms, and the ability to thrive in ambiguous environments with minimal oversight
- 3+ years of experience handling large data volumes and orchestrating and monitoring automated Batch & Near Real-Time ETL/data pipelines using CI/CD and Cloud Technologies, with preferred expertise in DBT or DBT Cloud
- Solid experience with MPP Data Warehouse systems such as Snowflake or Amazon Redshift, along with cloud platforms including AWS (Preferred), Azure, or GCP
Benefits
- Learn, grow, and succeed through innovation, collaboration, and exposure to what's next.
- Remote-first operating model with the freedom, autonomy, and trust to work from home and operate when most productive.
- Collaboration spaces for team members to work physically together when safe and when in-person collaboration delivers the best results.
- Remote hiring enabled in over 30 US states and several European countries, including Spain, Germany, the UK, Czech Republic, the Netherlands, and Switzerland.
Company Overview
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