Data Engineer

Company Description

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.

Job Description

Role: Data Engineer

Experience – 4 to 6 Years

Location - Pune

Skill Set & Technologies:
 

• Cloud-solutions (GCP), e.g. the following GCP specific tools: Google Cloud Storage, Big Lake, Big Query, Cloud Composer, Dataform
• SQL, Python, PySpark
• Software Engineering of DWH/BI solutions
• ETL/ELT solutions (also within classical SQL DWHs, like DB2/Oracle)
• Experiences with DWH typical technologies
• Experiences with tuning and optimization of ETL/ELT processes with bulk data
• CI/CD pipelines with GitLab

Experience & Requirement :
 

• Experiences with agile methods, like Kanban or Scrum
• Experiences with DWH typical data modelling, UML and meta based frameworks (e.g. Innovator)
• Implementation of efficient processes for the integration and consolidation of different data sources
• Data historization
• Versioning of software, state-of-the-art build- and deployment-methods, DevOps
• Intercultural experiences in near-/offshore-projects
• Analysis of business demands and experiences with the overall solution design of business demands.