Data Engineer

Jimdo

Build and maintain scalable data pipelines and transformations using dbt, SQL, Python, and Snowflake.
Develop and optimize data ingestion workflows, API integrations, and CDC pipelines using established engineering frameworks and best practices.
Implement data quality checks, testing, monitoring, and observability mechanisms to ensure reliable and trustworthy data products.
Design and maintain the foundational data layers, delivering clean, schema-enforced, contract-compliant, and analytics-ready upstream models for domain teams to leverage.
Leverage AI-powered development tools such as GitHub Copilot and Claude to improve productivity, code quality, and documentation.
Collaborate with analysts, BI teams, and stakeholders to define metrics, clarify business logic, and deliver impactful data solutions.
Contribute to data governance, compliance, and platform reliability by following data contracts, security standards, and engineering best practices.

4+ years of experience in Data Engineering, Analytics Engineering, or a related field.
Strong SQL skills, including complex joins, aggregations, CTEs, and window functions.
Hands-on experience with dbt for data transformation, testing, and documentation.
Practical experience with cloud data warehouses, preferably Snowflake.
Experience building data workflows and automation using Python.
Familiarity with orchestration tools such as Airflow and Git-based development workflows.
Strong problem-solving skills, attention to detail, and a collaborative mindset.
Experience with AWS services.
Exposure to data governance, data contracts, and compliance frameworks.
Experience using AI coding assistants and integrating AI into engineering workflows.
Familiarity with modern observability and monitoring practices for data platforms.