Data engineer állások, munkák it programozás, fejlesztés területen

• Architect and build the high-performance backbone of our data platform
• Focus on distributed computing stability and building effective caching strategies for large-scale operations
• Design ETL pipelines and architect resilient caching for complex dependency resolutions

• Design, develop, and optimize scalable data pipelines for processing large-scale structured and unstructured data
• Ensure reliability, performance, and scalability of data systems
• Build solutions to handle real-time streaming data from multiple sources

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations
• Provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Design, develop, and maintain scalable data pipelines in cloud and hybrid environments
• Contribute to the architecture of enterprise data platforms with a system-oriented mindset
• Work with large-scale datasets using SQL, Spark, and cloud-native tools

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

Senior Data Engineer Love what you do – we make employment happen! Turn data into impact! JobCloud connects hundreds of thousands of job seekers with employers every day and behind every product decision is data. As our next Senior Data Engineer, you'll own the warehouse stack that makes that...

• Architect and implement cloud-native data solutions using GCP (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Composer, Cloud Storage)
• Lead the design and development of complex data pipelines and distributed processing frameworks that ensure scalability, performance, and operational reliability

• Design, implement, and operate enterprise data platforms across on-premise, IaaS, PaaS, and SaaS environments
• Support and troubleshoot Cloudera Data Platform (CDP) environments, including upgrades and migrations

• Design and implement algorithms to process and analyze sensor data from sources like LiDAR, images, and satellite imagery
• Create algorithms to transform sensor data into actionable insights, such as reconstructing 3D models, segmenting spatial data, or detecting environmental features

Analysis of the data ecosystem: assessment of data systems, interfaces and data quality; evaluation of security / privacy and interoperability (data-level to user-level)...

Design, build, and operate database integrations and RESTful APIs for system and frontend integration, contributing to the conception and implementation of backend architectures for business applications....

• Managing and migrating ETL pipelines between various source systems
• Validating pipeline build success and output data quality
• Communicating with business stakeholders and SME's regarding their respective data domain
• Analysing and resolving blockers and issues with ETL pipelines and data discrepancies

• Build Data Pipelines: Design, build, and maintain scalable data pipelines for ingesting, transforming, and serving financial and operational data.
• Work with ERP Data: Integrate and model data from ERP systems and finance tools, including accounting, controlling, procurement, revenue, and cost data.

• Keep data moving: Build, run, and refine data pipelines and workflows (Python, Airflow/Cloud Composer) so they're reliable, fast, and easy to change
• Shape our data models: Use BigQueryand Cloud Spanner to design wellstructured, highperformance datasets for analytics and machinelearning use cases

• Experience in different data science topics
• Independent delivery of data science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

Partner with Marketing: Act as a strategic partner to the Marketing organisation and advocate for data-driven decision-making by effectively communicating AI strategy and its alignment with business objectives....

• Design, develop, and implement complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments
• Design, build, and optimize modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

• Design/build AI-ready Lakehouse architectures (Databricks, Fabric) and data pipelines for analytics/ML
• Develop financial data models (Data Vault 2.0) with governance (Purview, Unity Catalog)
• Architect AI infrastructure: Cognitive Search, RAG, vector DBs, knowledge graphs for agentic AI

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Integration of data ingestion, processing, transformation, and storage

• Design of Azure cloud infrastructure to support Databricks and data platform workloads
• Implementation and management of Azure cloud infrastructure
• Building and maintaining Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory integrations