• Progettazione, sviluppo e manutenzione di soluzioni per la generazione, raccolta, elaborazione e distribuzione dei dati. • Realizzazione e ottimizzazione di data pipeline. • Implementazione di processi ETL. • Presidio della qualità del dato, garantendo affidabilità, accessibilità e usabilità delle informazioni. • Collaborazione con team cross‑funzionali per supportare strategie data‑driven, contribuendo alle decisioni progettuali e al miglioramento continuo delle soluzioni dati in ambienti cloud moderni.

Role Description We are building a new, dedicated BI engineering team to take over and further develop a critical Business Intelligence component responsible for billing, reporting, and analytics across a wide range of sales and operational KPIs. As a BI Software Engineer – Data, you will focus on designing, developing, and operating data pipelines and reporting solutions. The component integrates customer, booking, and product data from multiple internal Magenta APIs (e.g. CDP, PIM, POM) and delivers structured outputs to various stakeholders and systems such as Data Warehouse (ODE), Billing, Kibana, and other analytics consumers. While the primary focus is on hands-on development, experience as a Product Owner and/or Business Analyst is considered a plus, but is not mandatory. Your Responsibilities - Design, implement, and maintain scalable BI and data processing solutions - Develop and operate ETL pipelines for customer, booking, and product data - Integrate data from various file- and REST-based Magenta APIs (like POM, PIM, CDP, PCM, etc.) - Generate and deliver reports and datasets for multiple downstream consumers (e.g. ODE, Billing, Kibana) - Collaborate closely with stakeholders across analytics, billing, and platform teams - Contribute to the setup and shaping of a newly formed team, including technical standards and best practices - Ensure data quality, reliability, and performance across the BI component - Support cloud-based operations and monitoring in an AWS environment Qualifications - Strong experience with ETL processes - SQL - Python - Docker - GitLab - Apache Airflow - Apache Cassandra - Kibana - AWS (general knowledge), including: - AWS S3 - AWS DataSync - AWS Athena Notebook - Amazon Aurora - Amazon ECS - Amazon ECR - PySpark - Experience with a data hub / data integration platform (Datendrehscheibe) - REST APIs (e.g. TARDIS / REST) Requirements - Experience in BI or billing-related data domains (Nice to Have) - Background as Product Owner and/or Business Analyst (Nice to Have) - Familiarity with data warehouse integrations (Nice to Have) - Experience working in cross-functional, agile teams (Nice to Have) - Knowledge of German is a plus, but not mandatory (Nice to Have) Benefits - The opportunity to build a new BI engineering team from the ground up - A technically challenging environment with modern data and cloud technologies - High impact on business-critical billing and reporting processes - Collaboration with diverse stakeholders across analytics and platform teams - An English-speaking work environment Company Description As Hungary’s most attractive employer in 2025 (according to Randstad’s representative survey), Deutsche Telekom IT Solutions is a subsidiary of the Deutsche Telekom Group. The company provides a wide portfolio of IT and telecommunications services with more than 5300 employees. We have hundreds of large customers, corporations in Germany and in other European countries. DT-ITS received the Best in Educational Cooperation award from HIPA in 2019, acknowledged as the Most Ethical Multinational Company in 2019. The company continuously develops its four sites in Budapest, Debrecen, Pécs and Szeged and is looking for skilled IT professionals to join its team.

• Design and build extraction, transformation, and loading (ETL) pipelines using Microsoft Fabric (Dataflow Gen2, Notebooks, or equivalent tools) • Write optimized SQL queries and transformations for data ingestion from designated source systems • Apply data quality rules and validation logic at each pipeline stage • Implement incremental loads and manage refresh schedules for performance • Escalate to Lead for architectural decisions or complex transformation patterns • Define and implement data quality checks at ingestion, transformation, and output stages • Perform ongoing data validation to ensure pipeline outputs align with business logic and source system expectations • Identify, document, and escalate data quality issues with root cause analysis • Maintain data quality dashboards and SLA monitoring • Support UAT for new data sources or transformation logic • Build and maintain data transformations using Power Query, SQL, or Python as appropriate • Develop dimensional models and define aggregation logic aligned with analytics requirements • Optimize data structures for performance and maintainability • Document transformation logic, lineage, and assumptions per team standards • Troubleshoot pipeline failures and performance issues; coordinate resolution with IT/Engineering • Respond to data discrepancy reports from business users and analysts • Maintain documentation of data sources, data dictionaries, and transformation specifications • Support capacity planning and optimization of Fabric environments and pipelines • Collaborate with Lead to define semantic models and calculated metrics

• Develop and maintain an OLAP ETL project using PL/SQL, AWS Glue (Python), RedShift • Support Java and Data Science development teams as an Oracle database expert • Develop and support other SQL and PL/SQL code existing in the platform