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Head of Data Analytics
Siemens
Siemens focuses on electrification, automation, and digitalization across various industries.
24d ago
Expert & Leadership (13+ years)
Full Time
Pune, Maharashtra, India
Office Full-Time
Company Size
303,000 Employees
Service Specialisms
Industry Automation
Power Transmission
Imaging & Therapy Systems
Diagnostics
Rail Systems
Mobility & Logistics
Low & Medium Voltage
Smart Grid
Sector Specialisms
Industrial Automation
Building Automation
Rail Transport
Health Technology
Factory Automation
Process Industries
Pharmaceuticals
Chemicals
Role
What you would be doing
team development
data stack innovation
dataops design
project management
client delivery
data architecture
Leading and developing an international team of 10 data experts to drive advanced analytics solutions.
Continuously innovating and improving the modern data stack by staying abreast of new data products, technologies, and innovations.
Leading the design and implementation of production-ready DataOps methods and pipelines.
Taking technical ownership of key data analytics projects and managing them with stakeholders from the business.
Create visibility for the team's activities and products, communicate successes and business value generated by applying modern data architecture and modeling frameworks
Shaping the overall data architecture, including standards for data models, metadata, and security.
Acting as a consultant, enabler, and mentor for internal customers and other data teams across Siemens Mobility to leverage digitalization and data-driven decision making
What you bring
degree
ci/cd
sql
python
data modeling
cloud
University degree in IT, Engineering, or a related field.
Familiarity with agile software development methodologies in the data and AI domain.
Profound understanding and experience with modern CI/CD pipelines.
Very good command of English; German is a plus.
Proven track record of leading and managing high-performing data teams.
Certifications in data architecture, data engineering, or data science disciplines, as well as knowledge of data governance frameworks and data quality management best practices, are a plus.
Expert programming skills in SQL and preferably Python.
Extensive experience with data modeling frameworks like Data Vault, Dimensional Modeling, Kimball & Inmon.
Working experience with major cloud technologies (AWS, GCP, Azure) and associated data warehousing and analytics tools (Snowflake, dbt Cloud).
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