Analytics állások XXIII. kerületben (adatbázisszakértő)

• Collaborate to the building, improvement and optimisation of the Customer Analytics process and related systems.
• Contribute to the development of the Customer Analytics Roadmap and translate it into actionable plans.

• Aktív részvétel a vállalat modern, Databricks‑alapú adatplatformjának fejlesztésében és üzemeltetésében
• ETL/ELT adatfeldolgozási és -betöltési folyamatok tervezése, fejlesztése és karbantartása különböző forrásrendszerekből származó strukturált és strukturálatlan adatokhoz

Act as the key link between business and delivery teams, ensuring alignment with enterprise standards (architecture, security, compliance) and providing clear visibility on progress, risks, and trade-offs to senior stakeholders....

• Design and maintain robust, scalable data architectures
• Build and optimize high‑performance data models for analytics
• Partner with business and engineering teams to shape data solutions end‑to‑end
• Lead data integration, transformation, and migration efforts

• Translate client needs into technical solutions 
• Design data-driven systems using Databricks and Azure 
• Build ingestion and transformation pipelines using SQL, Python, dbt 
• Automate data workflows 
• Participate in sprint planning and deliver reliable solutions 

• Data flow, data pipeline-ok és skálázható adatmodellek tervezése, fejlesztése és optimalizálása üzleti elemzések támogatására,
• Data martok üzemeltetése és karbantartása a domain szakértőkkel együttműködve,
• Oracle rendszerek előkészítése dbt és Snowflake alapú migrációhoz,

Dashboard development for sustainability data visualization Data integration from internal databases, external APIs, and third-party platforms Client reporting collaboration with sustainability team Data analysis to identify trends, patterns, and insights Quality assurance of data in dashboards and...

Data exploration, profiling, cleansing, and preprocessing for high-quality datasets Design and management of workflows for storing and retrieving vectorised documents Application of embedding models to build AI-driven solutions Leveraging modern AI and machine-learning techniques including large...

Maintaining and evolving existing data platform Building processes to ingest data from Kafka, APIs and Databases using AWS MSK Connect Development and maintenance of real-time data processing applications using frameworks like Spark Structured Streaming and Kafka Streams Applying transformations to...

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...

Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform Collaboration with the Architect in design discussions and proposals Building robust, scalable pipelines using Azure Databricks (PySpark / SQL) Integration of data ingestion, processing,...

Design Azure cloud infrastructure to support Databricks and data platform workloads Implement Azure cloud infrastructure to support Databricks and data platform workloads Manage Azure cloud infrastructure to support Databricks and data platform workloads Build Azure resources including Resource...

Setting technical direction across teams Driving AI-native and cloud-native architecture and long-term system evolution Leading design of secure, scalable MCP hosts and AWS microservices Balancing performance, reliability, and cost in system design Influencing AI adoption through AI first solution...

Ownership of data engineering features, architecture, and code quality Design, implementation, and maintenance of Databricks-based data pipelines and workflows Building and optimization of ETL/ELT processes using Apache Spark on Databricks Design and management of data lakes and Lakehouse...