• Design and build scalable data quality frameworks and validation systems that process financial data at enterprise scale and across diverse datasets • Own services end-to-end, from architecture and implementation through deployment and operational support • Build tools and interfaces that enable operations teams to efficiently identify, investigate, and resolve data issues • Design and deploy resilient, scalable cloud-native infrastructure on AWS using Terraform • Collaborate with cross-functional teams including product managers, data engineers, and operations stakeholders to deliver high-impact features • Work with modern data processing technologies like pySpark and Databricks to build, validate, and monitor data pipelines • Contribute to the broader Data Platform vision of making data discoverable, trustworthy, and actionable across Addepar

Role Description Join the Global Cloud Services organization's FinOps Tools team, which is building ServiceNow's next-generation analytics and financial governance platform. As the Distinguished Engineer for the FinOps Engineering Platform, you will set and own the technical vision and architecture for the entire platform. - Own the end-to-end technical architecture of the FinOps Engineering Platform. - Lead the design and development of the GCS Data Warehouse and the program to migrate ServiceNow's Global Cloud Services data platform off Cloudera onto the modern lakehouse. - Set the technical vision and multi-year roadmap for the platform. - Make the highest-leverage, hardest-to-reverse technical decisions. - Establish platform-wide engineering standards for reliability, determinism, observability, security, and production readiness. - Drive innovation across the platform, including the responsible use of AI/ML tooling. - Foster a culture of engineering craftsmanship, knowledge-sharing, and thoughtful quality practices. - Move fast while protecting the architectural integrity that lets it scale. Qualifications - Experience in leveraging or critically thinking about how to integrate AI into work processes. - 15+ years of experience in software or data engineering. - Proven track record as the lead architect or top technical authority for a platform. - Proven experience leading a large data platform migration or modernization. - Deep expertise across the modern data stack and in distributed-systems and cloud-native architecture. - Strong systems and backend engineering depth. - Hands-on experience with cloud cost management and FinOps. - Demonstrated ability to operate at high velocity in greenfield environments. - Strong knowledge of data structures, algorithms, and software quality principles. - Full professional proficiency in English. Requirements - Platform architecture: Designing and owning the architecture of large, multi-component platforms. - Modern data stack & lakehouse: Trino/Presto, dbt, Apache Iceberg, Lightdash. - Platform migration & modernization: Migrating off legacy Hadoop/Cloudera onto a modern lakehouse. - Forecasting & simulation: Deterministic, reproducible computation, multi-period simulation. - Cloud capacity & reservations: Hyperscaler capacity procurement. - Multi-cloud & infrastructure: Kubernetes, Infrastructure as Code, CI/CD. - Reliability & observability: SLI/SLO/error-budget design. - Data contracts & quality: Fail-loud ingestion and correctness invariants. - API & integration design: RESTful services and webhook/event integrations. Benefits - Base pay of $221,200 - $387,100, plus equity and variable/incentive compensation. - Health plans, including flexible spending accounts. - 401(k) Plan with company match. - ESPP and matching donations. - Flexible time away plan and family leave programs.

• Diseñar modelos de datos • Explotar la información mediante las herramientas designadas • Interactuar con los clientes para entender sus requisitos y proporcionar soluciones • Preparar documentación técnica de las soluciones proporcionadas • Asegurar la calidad y la exactitud de los datos en los informes

Role Description Our Data Tribe's mission is to deliver business value in all strategic areas of TDG to become a real data-driven company. In the Data Domain Consumer, we focus on Deutsche Telekom's private customers and create exceptional consumer experiences by harnessing and analyzing data to drive insights-based decision-making. - Provide personalized customer dialogue at every touchpoint. - Ensure omni-channel engagement with the customer at the center of data-driven actions and offers. - Establish and maintain a single source of truth around our customer. - Ensure a unified data flow of TV-relevant data across different systems for holistic analytics. - Focus on customer experience activities, including NPS analytics and dashboards. - Provide data analytics use cases for digital touchpoints of the German NatCo. - Establish common practices for generative AI use cases. As a data engineer, you will be responsible for: - Developing and operating our data pipelines. - Building data layers in OneDataLake (ODL), our Central Data Store Consumer (CDSC). - Balancing business and IT demands to build modern and efficient pipelines in public cloud environments. - Integrating data preparations into managed processes. - Implementing data integrations in Data Vault. - Managing data exports and data operations. Technologies used include Python, PySpark, SQL, and libraries such as Pandas, Matplotlib, Seaborn, Bokeh, Plotly, with pipelines based on Gitlab (Magenta CI/CD). Qualifications - Minimum 3+ years of professional experience as a Data Engineer with proven expertise in big data pipelines and data processing. - Advanced proficiency in SQL, Python, and PySpark for hands-on data transformation and pipeline development. - Demonstrated experience with Git version control and CI/CD practices. - Strong capability to design, build, operate, and troubleshoot data pipelines in production environments. - Proven ability to understand complex data structures and transform them into required structural formats. - Business-fluent English language skills. Requirements - Senior-level experience or equivalent seniority in data engineering. - Hands-on experience with Google Cloud Platform (GCP) technology stack. - Familiarity with Hadoop ecosystem and related big data technologies. - Experience with data modelling, exploration, and architecture within enterprise environments. - German language proficiency. Key Competencies - Practical, hands-on approach to problem-solving (not purely conceptual or advisory). - Ability to quickly assimilate complex data environments and deliver solutions. - Experience integrating data preparations into managed processes and implementing Data Vault integrations. - Familiarity with data visualisation libraries such as Pandas, Matplotlib, Seaborn, Bokeh, and Plotly. Benefits - Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation. 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. - Hundreds of large customers, corporations in Germany and other European countries. - Received the Best in Educational Cooperation award from HIPA in 2019. - Acknowledged as the Most Ethical Multinational Company in 2019. - Continuously develops its four sites in Budapest, Debrecen, Pécs, and Szeged. - Looking for skilled IT professionals to join its team.