Mid Data Engineer

As a Data Engineer, you'll be a hands-on contributor within our Data Platform team, building and maintaining the pipelines, models, and integrations that drive data-informed decision-making across Jimdo. Reporting to the Data Platform Manager, you'll own well-defined projects end-to-end—from implementation and testing through monitoring and optimization—while collaborating closely with senior engineers, analysts, and stakeholders. This role offers the opportunity to work with a modern cloud data stack including Snowflake, dbt, Airflow, AWS, and AI-powered engineering tools.

Responsibilities

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

Requirements

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

Benefits

Fully remote work set-up; opportunities for in-person collaboration; flexible working hours; international diverse team; Employee-led DEI Council; active ERGs; LinkedIn Learning; Hack Weeks; Deep Work Thursdays; conferences; technical eLearning platforms; annual compensation reviews; remote office set-up bonus; employee assistance program; up to three free Jimdo websites