Senior Data Engineer
Design and build scalable, reliable data platforms using Azure Databricks and Delta Lake. Collaborate with cross-functional teams to turn business requirements into efficient data pipelines and models.
Remote Data Engineer Jobs in Germany
81 Data Engineer jobs in Germany available for remote work from home. Apply for positions such as Senior Data Engineer, Data Engineer, Freelance Senior Quantexa Data Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and build scalable, reliable data platforms using Azure Databricks and Delta Lake. Collaborate with cross-functional teams to turn business requirements into efficient data pipelines and models.
The Data Engineer will design and maintain robust ETL pipelines and optimize relational databases to support business intelligence. They will also develop interactive Power BI dashboards and ensure data integrity through rigorous validation and reconciliation.
Design, develop, and implement complex software solutions using the Quantexa platform. Collaborate with cross-functional teams to ensure high performance, scalability, and reliability of software deliverables.
You will be responsible for building and maintaining data models, Clickhouse aggregations, and event-driven streaming applications to support internal analytics and product features. Additionally, you will harden the Kafka ecosystem and develop data lake architectures for long-term storage and disaster recovery.
Build and maintain scalable data pipelines using Azure Databricks, PySpark, and SQL while developing Bronze, Silver, and Gold data layers. Collaborate with cross-functional teams to implement data validation, quality checks, and production-ready analytics solutions.
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You will design and own a multi-source data platform, managing everything from architecture and ingestion to production operations. Responsibilities include building robust data pipelines, orchestrating workflows, and implementing data quality monitoring.
Design, build, and manage scalable multi-cloud data platforms while developing real-time and batch data pipelines. Drive technical architecture, mentor engineering staff, and ensure high standards for data reliability and security.
Lead the migration of data into a modern Databricks/Azure architecture while designing and optimizing scalable data pipelines. Collaborate with global stakeholders to ensure data quality, security, and effective reporting enablement.
You will own data engineering projects end-to-end, collaborating with Product Managers to define requirements and implement scalable solutions. Additionally, you will focus on system performance and stability while participating in code reviews to ensure high-quality, maintainable code.
Design, build, and optimize robust data pipelines to create scalable, high-value data products. Collaborate with business stakeholders and engineering teams to bridge technical data architecture with business applications.
Develop and optimize enterprise ETL/ELT pipelines with Talend and Apache Spark, and write performant SQL for large-scale datasets. Collaborate with solution architects on governance, schema management, and data quality, while troubleshooting distributed jobs and documenting work within an Agile team.
The role involves designing and maintaining ETL/ELT processes while integrating new data sources into the product. You will also be responsible for building analytical data models and ensuring the quality, consistency, and traceability of information.
The role involves co-developing batch and streaming data pipelines on Databricks and defining data contracts and quality rules. You will also mentor domain engineers on data product ownership and best engineering practices.
Build and maintain automated ETL pipelines to integrate marketing platforms and CRMs into a central database. Develop and manage data dashboards while automating recurring business reports and analyzing performance metrics.
You will model complex data, build evaluation harnesses for AI agents, and maintain robust data pipelines. You will also collaborate with product and ML teams to ensure data quality and integrate new data sources.
Design, build, and manage scalable multi-cloud data platforms while developing real-time and batch data pipelines. Ensure high standards of data reliability, security, and governance while mentoring engineering team members.
The Data Engineer designs, builds, and maintains scalable data infrastructure and ETL pipelines to support digital marketing strategies. They ensure data integrity and quality while collaborating with cross-functional teams to prepare data for dashboards and reporting.
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Own and develop the company’s analytics infrastructure, including data collection, ETL/ELT pipelines, orchestration, backfills, monitoring, and integrations with marketing, billing, product, and internal data sources. Build and maintain dbt models, implement data quality controls, and document data sources, models, and business logic for analytics teams.
Design, develop, and maintain batch and event-driven data pipelines while optimizing IBM DB2 database performance. Collaborate with cross-functional teams to integrate legacy systems with modern cloud platforms and ensure data reliability.
Design, build, and maintain scalable batch and streaming data pipelines, transforming data from diverse sources into governed, analytics-ready datasets and reusable data services. Collaborate with clients, analysts, data scientists, and architects to ensure data quality, security, governance, performance, and clear technical documentation.
Design and build reliable, high-performance data architectures, managing the process from source integration and transformation through modeling and delivery for applications, dashboards, and analytics. Automate data imports, deployments, quality checks, and alerts; collaborate with product and engineering teams; mentor colleagues; and advise on AI-related workflows and solutions.
You will design and implement the target architecture for a new data warehouse on BigQuery, managing the entire pipeline from raw data to data marts. Additionally, you will establish data quality standards, develop dbt models, and build a semantic layer to support both business intelligence and AI applications.
The Senior Data Engineer will design, develop, and maintain scalable ETL/ELT pipelines while managing AWS workflows and orchestration tools. Additionally, the role involves leading a small team, collaborating with cross-functional stakeholders, and implementing AI-driven automation for engineering tasks.
You will develop modern data platforms and pipelines using Databricks and cloud technologies while integrating data from various source systems. Additionally, you will optimize ETL/ELT processes and collaborate closely with data architects and analytics teams to support technical decision-making.
You will design, implement, and operate scalable data pipelines and Lakehouse solutions using Databricks and modern cloud technologies. Additionally, you will contribute to the company academy by conducting workshops and sharing technical expertise with clients and team members.
The Data Engineer will design, build, and maintain scalable data pipelines and ETL/ELT processes to integrate multiple data sources. They will also ensure data quality and collaborate with cross-functional teams to support analytics and data-driven decision-making.
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Design, develop, and optimize scalable data pipelines using Azure Data Factory and other cloud-native services. Implement secure data migration strategies, including encryption and masking, while ensuring reliable performance across Azure environments.
You will architect and lead the development of large-scale data pipelines and streaming systems to process billions of daily events. Additionally, you will own production data systems, ensuring high uptime, reliability, and scalability while collaborating with cross-functional teams.
Develop and maintain scalable ETL/ELT data pipelines while ensuring data quality, governance, and reliability for CRM and analytics teams. Collaborate with business units to model data and integrate it with engagement platforms to support customer journey automation.
You will design, develop, and operate modern, scalable cloud-based data platforms and pipelines. Additionally, you will ensure data quality, security, and stable production operations while mentoring less experienced team members.
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