Python programmer állások, munkák adatbázisszakértő kategóriában

• Development and optimization of large-scale data processing workflows using Apache Spark, PySpark, and SQL
• Building and enhancing multi-stage ETL pipelines with idempotency and failure recovery
• Implementation and configuration of pipeline orchestration using Airflow, Dagster, or Prefect

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Development, testing, and maintenance of data pipelines to extract, transform, and load (ETL) data from various sources
• Writing high-quality, maintainable Python code
• Participation in code reviews
• Participation in technical discussions for tool selection and architectural decisions

• Design and implement enterprise-scale data pipelines and advanced analytics dashboards
• Develop and optimize data ingestion, transformation, and modeling workflows across structured data environments and cloud-based platforms

Partner with Product teams to define, monitor, and investigate KPIs, and deliver deep-dive analyses that explain what is driving user behavior and product performance, translating findings into clear recommendations....

• Developing concepts for surgical 3D scene understanding and computer-assisted surgery, with a focus on 4D Gaussian Splatting, stereo and surface reconstruction, and multimodal sensor fusion
• Evaluating concepts on curated datasets and in own lab experiment settings

• Extract meaningful insights from complex datasets using advanced AI, analytics techniques, and data visualization.
• Translate insights into strategic recommendations to foster data-driven decision-making.

• Own the end-to-end forecasting and price-elasticity models at the core of our pricing engine — from feature and model research through evaluation, deployment, and continuous monitoring
• Scale the forecasting architecture to meet growing demand for granular, product-level forecasts

• Technikai menedzsment és fejlesztés a csapat felhőalapú adatplatformján és adatmodellein Azure Databricks környezetben
• A Data-Driven Project Modelling (DPM) motor fejlesztése és karbantartása DevOps legjobb gyakorlatok szerint

Design and maintain scalable Lakehouse architectures and data pipelines using Azure Data Factory, Databricks, and Microsoft Fabric to support analytics and AI products....

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Define the data, training, and experimentation environment to enable scalable access to data and compute.

• Contribute to pioneering technical advances to the field of foundation models on structured data, as well as exploring world models for solving business problems.
• Execute scientific experiments on internal as well as public data.

• Collaborate with business stakeholders and leadership teams to gather requirements, develop, and support data modelling and BI solutions for organizational stakeholders
• Integrate different data sources into a cohesive data fabric, ensuring data consistency, accuracy and reliability

Where you belong: Where you belong: ...

• Designing, implementing, testing, and optimizing reliable, efficient, and high-quality data pipelines
• Automating the extraction, loading and transformation of data from a wide variety of sources
• Developing solutions for the automated acquisition of data from source systems

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

• Design, build, and deploy end-to-end machine learning algorithms for complex data challenges
• Develop identity resolution algorithms and refine for accuracy and performance at scale
• Support production deployment of machine learning algorithms

• Design and implement pipelines to ingest, clean, and transform data into Data Lakes and Data Warehouses
• Active monitoring and optimization of pipelines for performance and cost
• Configuration of pipeline deployments and management of environment settings using IaC tools and CI/CD