We build data product sharing software which fuels AI.Monda believes that any company should be able to share and access the data they need to fuel AI. Therefore we create a borderless data sharing ecosystem to fuel the AI revolution and accelerate human progress. We encourage and empower any company in the world to share and monetize their data safely.Our Engineering Team:We are a passionate, multicultural engineering team dedicated to turning complex data challenges into seamless software — always deciding, acting, and delivering with the customer experience at the core.Our Data Tech Stack:Snowflake, Prefect, Python, Django, AWS, Terraform, Cloudflare, Docker, Github, HerokuOur Tech Challenges:Simplify cross-cloud data product creation: Enable easy onboarding of data sources from multiple cloud environments and ensure reliable data delivery for true cross-cloud sharing, supporting seamless data marketplace integrations across AWS, GCP, Azure, Snowflake, and Databricks.Fuel the AI revolution: Streamline data customization and multi-asset data product management, empowering integrations with leading data marketplaces such as Datarade, Snowflake Marketplace, Databricks, Google Cloud Analytics Hub, and SAP Datasphere. Drive innovation in data platforms: Tackle the challenges of scalability, reliability, and performance in a rapidly evolving, multi-cloud ecosystem while enabling business-ready, high-quality data products.TasksWe're looking for a Senior Data Engineer (d/f/m) to join our software engineering team in Berlin. As an individual contributor (IC), you'll work closely with our Head of Engineering. You'll not only develop new cross-cloud data sharing features from scratch but also improve the stability of the platform and all data pipelines.The start date is 1st of January 2026, work location is Berlin (hybrid), base salary starts at €75K gross / annum (based on experience).What you'll do:Enable customers to connect diverse data sources and publish marketplace-ready data products, fueling seamless data exchange and monetizationEnsure solid, observable, and efficient data flows by operating Python pipelines orchestrated with Prefect and running on AWS ECSConnect and unify data across multiple cloud environments, enabling secure and high-performance data exchange between diverse customer systems and platformsCollaborate across teams to align technical solutions with customer and business needs, driving engineering excellence and platform reliabilityDesign, develop, and maintain our Snowflake-based cross-cloud data platform with scalable and future-proof architectureRequirementsMinimum qualifications:5+ years of hands-on experience as a Data Engineer or in a similar role, building and maintaining large-scale data systems in Snowflake environmentExpert knowledge of Snowflake and Python, with experience designing efficient, scalable, and secure data pipelinesProficiency in data orchestration frameworks such as Airflow, Dagster, or dbt — experience with Prefect is a strong plusSolid understanding of containerization and cloud infrastructure, particularly with Docker and AWS ECSProven experience in data platform architecture, data delivery, and data lifecycle best practicesStrong sense of ownership and accountability, with the ability to prioritize, assess criticality, and deliver results under minimal supervisionExperience working in agile, cross-functional teams, embracing iterative development and continuous improvementBonus qualifications:Degree in Computer Science, Information Systems, Application Programming, or a related technical fieldHands-on experience with Infrastructure as Code (IaC) tools such as TerraformBackground in international B2B software applications, ideally within the e-commerce industryIn-depth knowledge of multiple cloud service providers (e.g., AWS, GCP, Azure) and experience working in cross-cloud environmentsGenuine passion for Data Engineering, with additional experience in web application development or adjacent software domainsWe’d love to hear from you! Apply now and expect a fast, transparent hiring process: a quick intro call, a focused code challenge, and conversations with the team and founders.