Data Engineer (Apache Flink)
Design and operate high-volume, low-latency real-time data systems using Apache Flink as the core engine. Build and maintain high-scale streaming data pipelines on self-managed on-premise infrastructure.
Remote Data Engineer Jobs in Czech Republic
48 Data Engineer jobs in Czech Republic available for remote work from home. Apply for positions such as Data Engineer (Apache Flink), Data Engineer (Apache Spark), Senior Data Engineer - Web Scraping and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Design and operate high-volume, low-latency real-time data systems using Apache Flink as the core engine. Build and maintain high-scale streaming data pipelines on self-managed on-premise infrastructure.
Design and operate high-volume analytical data systems end to end using Apache Spark. Build and maintain high-scale batch and near-real-time data pipelines on self-managed infrastructure.
Design, implement, and maintain web scrapers to collect alternative datasets while performing data cleaning and transformation. Collaborate with cross-functional teams to build efficient data processing workflows and maintain alerting systems for data integrity.
Design, build, and maintain scalable data pipelines while leveraging tools like Azure Data Factory and Databricks. Lead and mentor engineering teams while collaborating with cross-functional stakeholders to deliver comprehensive data solutions.
Design and maintain scalable data pipelines using Databricks to support HR and People Analytics. Develop interactive Power BI dashboards and optimize data models to provide actionable workforce insights.
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Build and scale data platforms for AI-driven analytics using high-volume sensor, satellite, and third-party data. Own end-to-end data pipelines from real-time ingestion to analytics while ensuring data quality and performance.
Lead the implementation of a scalable data quality and observability framework using GX Core to detect and prevent data issues. Design automated validation checks, maintain data lineage, and integrate quality validations into CI/CD pipelines.
Design, develop, and deploy scalable data pipelines and ETL/ELT processes using the Dataiku DSS platform. Support a large-scale enterprise data lakehouse migration while collaborating with international business and technical stakeholders.
Architect and maintain the data model, pipelines, and access layers to support healthcare operations and analytics. Lead technical engineering best practices and ensure data quality and governance across the platform.
Design and optimize robust data pipelines and scalable warehousing architectures using Snowflake and dbt. Collaborate with stakeholders to transform raw data into actionable models for manufacturing and supply chain workflows.
Develop and maintain the Enterprise Data Warehouse and standard dashboards for a Global Business Intelligence Team. Provide data support for business self-service and data analysis activities.
Design and maintain scalable ETL/ELT pipelines to extract and load data from sources like Oracle. Create and optimize data models in Snowflake and Redshift to support AI/ML solutions and business objectives.
Design, develop, and deploy bots using Automation Anywhere A360 and Excel VBA macros. Collaborate with stakeholders to identify automation opportunities and maintain documentation such as PDDs and SDDs.
Design and maintain scalable batch and real-time data pipelines on GCP using Medallion Architecture. Develop high-performance data transformations and optimize complex SQL queries for large-scale analytical workloads.
Architect and lead operational data flows and the analytical ecosystem, focusing on real-time data streams and scalable ELT patterns. Mentor a high-performing engineering team while partnering with leadership to translate technical roadmaps into business value.
Design and optimize complex SQL Server solutions with a focus on performance tuning and data modeling. Automate processes using PowerShell and integrate systems via APIs and LLM-driven workflows.
The role involves leading the development and maintenance of data services and solutions to support products, downstream services, or infrastructure tools used across BEES. This includes designing efficient data models and implementing architectural improvements to enhance performance, monitoring, and evolution of data products.
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The Data Engineer will design, optimize, and own data pipelines that scrape, process, and ingest transaction and listing data. They will also build monitoring systems to track data metrics and continuously improve the data infrastructure.
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