Development állások Budapesten (adatbázisszakértő)

• Design, development, and continuous improvement of the Data Warehouse environment 
• Development and optimization of ETL processes
• Administration and operation of complex SQL cluster environments 
• Re-engineering and modernization of existing SQL cluster architectures

• Assist in the development and maintenance of RPA solutions to automate business processes.
• Collaborate with stakeholders to identify automation opportunities and enhance existing workflows.
• Build and manage Power BI reports to monitor automation performance.

• Design and implement a QC-sample-data strategy to support longitudinal comparability
• Define acceptance criteria and evaluate instrument performance, signal drift, and technical variation across batches and years

• Learn Generative AI principles and models
• Learn Large Language Models, Natural language processing
• Work with Different generative AI Tools and uses
• Learn the LLMs, NLP fundamentals, Transformers, and attention mechanism
• Build Custom dataset for LLM, Build your own custom chatbot/AI bot/custom GPT

• learning state‑of‑the‑art new technologies
• acting as a team member in BI‑focused engagements

• Collaborate with internal and external stakeholders to identify digital solutions by analyzing processes and evaluating the feasibility of automation or reporting.
• Extract, summarize, and clean raw data to create valuable reports.

• Design, build, and maintain robust data pipelines that are scalable, efficient, and meet business needs
• Collaborate with cross-functional teams to understand and translate business requirements into data solutions

• Learn data engineering principles
• Learn to design and implement ETL processes and pipelines
• Work with SQL, Python and different programming languages and notebooks
• Learn Power BI report building, Data Bricks and various ETL tools

• Own and oversee Global Data Platforms (Power BI, AWS, Snowflake), ensuring secure, reliable, and high-performing services
• Monitor, analyse, and report cloud usage and costs, driving transparency and cost optimisation

Assessment/blueprinting of enhancements and projects providing ensuring solutions meet or exceed business value propositions and meet architectural policies....

Design, implement and enhance data solutions for customer organizations Implementation of data integrations (e.g. load data from operative systems like ERP or CRM) Development of data platform / data warehouse in cloud platforms (e.g. data transformation and aggregation) Implementing...

Work in cross-functional agile teams alongside data scientists, machine learning engineers, product managers, and industry experts to innovate with clients and consulting teams Design and build robust, modular, scalable, and secure data pipelines for machine learning that are deployable,...

Designing and developing platform to fulfil business needs Design new data pipelines Maintain platforms hosted on data streams for batch-loading and real-time visualisations Maintaining and evolving existing data platform Follow and mentor engineers on data modelling following standards e.g. Inmon,...

Lead or participate in scoping the engagement, designing high-level architecture, defining subtasks, and project delivery schedules Deliver projects independently or within a mixed DS/DE team, often as technical lead Act as client-facing interface or SPOC to customers Provide ML/DS consultancy 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...

Maintaining and evolving our Data Structures Build new ETL flows and maintain/improve existing ones Be part of designing new data structures and data modelling concepts Ensure data quality by verifying data consistency and accuracy – being able to create data validation methods Write, optimize, and...

Implement and maintain large‑scale data pipelines and the Azure/Databricks data platform in close collaboration with the Architect, contributing to design discussions and proposals. Build robust, scalable pipelines using Azure Databricks (PySpark / SQL), integrating data ingestion, processing,...

Design, implement, and manage Azure cloud infrastructure to support Databricks and data platform workloads Build and maintain Azure resources including Resource Groups, VNets, Key Vaults, Storage Accounts, and Azure Active Directory (AAD) integrations Implement Infrastructure as Code (IaC) using...

Design, write and execute comprehensive test plans, test cases and test scripts to validate ETL/data‑pipeline processes, data transformations, and data integrity (source‑to‑target, cross‑reference, reconciliation). Validate data extraction, transformation and loading processes for accuracy,...