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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - Mobile Apps - **Company:** Jobgether - **Location:** Netherlands (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Google AdWords, Agile Methodology, Airflow, Data Analysis, BigQuery, Data Validation, Information Engineering, Data Infrastructure, Data Systems, Payment Systems, Mobile Application Software, Python (Programming Language), Operational Databases, SQL Databases, Workflow Management Systems, Google Cloud, Apache Spark, Stripe, Data Pipelines, Databricks - **Published:** September 14, 2026 - **Apply:** https://www.adzuna.nl/details/5882782120 ## About the Role * Proven experience in data engineering, with strong hands-on expertise in Python, SQL, Spark, and Databricks. * Experience working with Databricks technologies such as Unity Catalog and Delta. * Practical experience with Apache Airflow for workflow orchestration and scheduled production data pipelines. * Experience with Google Cloud Platform, particularly Google Cloud Storage (GCS) and BigQuery. * Strong analytical and problem-solving abilities, with a strategic and structured approach to resolving complex technical challenges. * Experience taking ownership of production data environments, including scheduled jobs, data quality checks, alerting, monitoring, and incident resolution. * Strong collaboration and communication skills, with the ability to work effectively with cross-functional stakeholders at different levels. * Advanced English proficiency, both written and spoken, for clear communication in an international working environment. * Solid understanding of agile methodologies and the ability to manage multiple projects without compromising quality. * Curiosity about the business context behind data, with an interest in areas such as marketing spend, subscriptions, payments, and attribution. * Experience with dbt and APIs from advertising or payment platforms such as Google Ads, Stripe, RevenueCat, or similar is a plus. ## Description As a Senior Data Engineer, you will help build and operate reliable data infrastructure that supports marketing, payments, product analytics, and business decision-making. You will design and maintain data pipelines that ingest information from advertising platforms, payment systems, and product backends into modern cloud data environments. The role combines hands-on engineering with production ownership, ensuring critical reporting, attribution, and LTV data remains accurate and available on time. You will work closely with Analytics, Marketing, Data Science, Product, and Engineering teams to translate business needs into scalable data solutions. You will troubleshoot complex pipeline issues, strengthen data quality, and continuously improve the reliability and efficiency of data processes. Beyond the technology, you will develop a strong understanding of the business context behind the data, including marketing spend, subscriptions, and attribution. This is an opportunity to make a direct impact in a collaborative, international environment while working with modern data engineering technologies. Accountabilities: * Build, maintain, and operate reliable data pipelines that support daily reporting, attribution, LTV analysis, and other critical business use cases. * Ingest and transform data from advertising platforms, payment systems, and product backends into Databricks-based data environments. * Orchestrate scheduled data workflows using Apache Airflow and ensure critical jobs complete accurately and on time. * Maintain accurate and reliable silver and gold data tables while implementing appropriate data quality checks and monitoring. * Proactively identify, troubleshoot, and resolve pipeline and production issues, including recovering failed daily runs within required timelines. * Develop and improve processes, tools, and data solutions that enhance operational efficiency and support evolving business requirements. * Collaborate with Analytics, Marketing, Data Science, Product, Engineering, and other stakeholders to understand requirements and evaluate technical approaches. * Balance multiple projects and priorities while maintaining high standards of data quality, reliability, and delivery. * Contribute to the continuous improvement of data engineering practices, processes, and methodologies within an agile environment. * Apply a business-oriented perspective to data engineering, understanding how marketing investment, subscriptions, payments, and attribution influence organizational performance. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Navigating Growth, Scaling Challenges, and Office Expansions with David Singleton, CTO at Stripe](https://www.wearedevelopers.com/videos/100362-navigating-growth-scaling-challenges-and-office-expansions-with-david-singleton-cto-at-stripe) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Making Data Warehouses fast. 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