Senior Data Lead architect (REF2159Z)
Budapest, Hungary
Deutsche Telekom IT Solutions
Deutsche Telekom TSI Hungary Kft., Deutsche Telekom ITTC Hungary Kft.Company Description
The largest ICT employer in Hungary, Deutsche Telekom IT Solutions (formerly IT-Services Hungary, ITSH) is a subsidiary of the Deutsche Telekom Group. Established in 2006, the company provides a wide portfolio of IT and telecommunications services with more than 5000 employees. ITSH was awarded with the Best in Educational Cooperation prize by HIPA in 2019, acknowledged as one of the most attractive workplaces by PwC Hungary’s independent survey in 2021 and rewarded with the title of 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.
Job Description
We are seeking an experienced and highly skilled Senior Data Architect to join our dynamic and innovative team. As a Senior Data Architect, you will play a pivotal role in shaping and implementing our data architecture strategy, ensuring the efficient and effective management of our Data Tribe data assets. This role requires a deep understanding of data modeling, database design, data warehousing, data analytics, data integration and data products, as well as a proven track record of successfully leading complex data architecture initiatives.
Responsibilities:
Data Architecture Strategy:
Develop and drive the overall data architecture strategy in alignment with the organization's business objectives.
Collaborate with stakeholders to understand data requirements and translate them into comprehensive and scalable data solutions.
Data Architecture Planning:
Develop and maintain a comprehensive data architecture roadmap, considering both short-term goals and long-term vision.
Evaluate and recommend technologies and tools that align with the organization's evolving data needs.
Data Modeling and Design:
Oversee the design and implementation of robust data models that meet the organization's current and future requirements.
Design and implement robust data models that support both transactional and analytical requirements.
Ensure data integrity, consistency, and accuracy across various databases and data sources.
Ensure data models adhere to industry best practices and standards.
Data Integration:
Oversee the integration of data from various sources, ensuring seamless and accurate data flow.
Implement data integration solutions that support real-time and batch processing requirements.
Establish and enforce data management policies and procedures to ensure data quality, consistency, and security.
Collaboration and Communication:
Collaborate with cross-functional teams, including data scientists, analysts, and software engineers, to ensure a cohesive and integrated approach to data management.
Provide technical leadership and mentorship to junior members of the data architecture team.
Communicate complex technical concepts to non-technical stakeholders in a clear and understandable manner.
Data Governance and Security:
Establish and enforce data governance policies and procedures to ensure data quality and compliance.
Implement robust security measures to protect sensitive data assets.
Continuous Improvement:
Stay current with industry trends and emerging technologies related to data architecture.
Identify opportunities for continuous improvement and optimization of data-related processes.
Qualifications
Qualifications:
Bachelor's or Master's degree in Computer Science, Information Systems, or a related field.
Proven experience as a Data Architect or a similar role, with a minimum of 4 years of relevant experience.
Certification in Google Cloud Professional Data Engineer or related GCP certifications is highly desirable.
Proficiency in designing and implementing data solutions on Google Cloud Platform.
Strong expertise in GCP data services, including BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
Experience with data modeling tools specific to GCP, such as BigQuery ML and Data Catalog.
In-depth knowledge of GCP security and compliance features related to data management.
Extensive experience in designing and managing databases on GCP, including Cloud SQL and Cloud Spanner.
Proven ability to architect and implement data warehousing solutions on BigQuery.
Familiarity with GCP's NoSQL database offerings, such as Iceberg and Bigtable.
Demonstrated experience in building and optimizing data integration pipelines using GCP Dataflow.
Proficient in GCP's data transfer and ingestion tools, such as Transfer Service and Cloud Storage Transfer Service.
Ability to integrate and synchronize data between on-premises and GCP environments.
Experience in leveraging GCP tools for advanced analytics and reporting, including Data Studio and Looker.
Knowledge of data visualization tools and techniques on GCP.
Familiarity with GCP's data governance and compliance features, including Data Loss Prevention (DLP) and Cloud Identity and Access Management (IAM).
Proven ability to implement and enforce data governance policies and procedures on GCP.
Strong collaboration skills to work effectively with cross-functional teams and stakeholders.
Excellent communication skills to convey complex technical concepts to both technical and non-technical audiences.
Exceptional problem-solving and analytical abilities to identify and address complex data architecture challenges.
Proactive in identifying opportunities for optimization and efficiency improvements within the GCP data environment.
Additional Information
Additionally, our way of working requires that you be a Team player with great Communication Skills, able to travel and produce out of the box ideas.
* Please be informed that our remote working possibility is only available within Hungary due to European taxation regulation.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture BigQuery Bigtable Computer Science Data Analytics Dataflow Data governance Data management Data quality Data Studio Data visualization Data Warehousing GCP Google Cloud Looker Machine Learning NoSQL Pipelines Security SQL
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