T-Systems Information and Communication Technology India Private Limited (T-Systems ICT India Pvt. Ltd.) is a proud recipient of the prestigious Great Place To Work® Certification™. As a wholly owned subsidiary of T-Systems International GmbH, T-Systems India operates across Pune, Bangalore, and Nagpur, boasting a dedicated team of 3500+ employees providing services to group customers. T-Systems offers integrated end-to-end IT solutions, driving the digital transformation of companies in all industries, including automotive, manufacturing, logistics, and transportation, as well as healthcare and the public sector. T-Systems develops vertical, company-specific software solutions for these sectors. T-Systems International GmbH is an information technology and digital transformation company with a presence in over 20 countries and a revenue of more than €4 billion. T-Systems is a world-leading provider of digital services and has over 20 years of experience in the transformation and management of IT systems. As a subsidiary of Deutsche Telekom and a market leader in Germany, T-Systems International offers secure, integrated information technology and digital solutions from a single source.

Role : System Architect (Senior Data Architect / Modeler)

Experience : 12+ Years

Location : Pune

Job Description :

Mandatory skills:

Data Architecture, Data Modelling, Data Integration, Data Catalog and Governance, Cloud experience (GCP initially, if we exhaust with profiles then we can extend it to other clouds), experience on Spark, Kafka, Collaborate with cross-functional teams

Good to have: Telecom data domain knowledge.

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.