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Job Description & How to Apply Below
Creative Synergies Group Overview:
Creative is a leading global technology services firm delivering innovative solutions that synergise our deep engineering domain expertise and Digital Engineering Services
Creative’s global team of 1,600+ “Can-Do” engineers collaborate with our 40+ Fortune 500 clients to help them achieve their strategic and operational objectives (Including Google, Tesla, Samsung, Mercedes, Toyota, Mitsubishi, Hitachi)
95% of our revenues accrue from US, Europe, Japan based customers
We work with clients across the global Transportation, Energy/Process, Industrial Products, Hi-Tech, Ed-Tech Industries.
Service Offerings:
Al/ML and Digital Technologies:
Agentic AI
GenAI Business Services
AI/ML
Data Analytics and Data Engineering
Cloud Technologies
Application Development
Digital Platform Engineering
Cybersecurity
Intelligent Connected Products:
Edge Analytics
Industrial and Consumer IoT
Platform Development
Mobile Robotics
Vehicle Centric Electronics
Connected Car and Telematics Solutions
Digital Manufacturing:
Digital Plant Engineering:
Founder / CEO:
Dr. Mukesh Gandhi
Former Michigan State University Professor(1984 - 1999)
Published Ground-Breaking Technical Publications and Books Supervised PhD, Masters and Undergraduate Research Students - Who Are Now Leaders and Decision Makers in Industry and Academia
Awarded Over $15 Million For Pioneering Research from National Science Foundation (NSF), US Army Research Office (ARO), Defense Advanced Research Projects Agency (DARPA), US National Institute of Standards and Technology (NIST)
Founder / CEO of Quantech Global Services
Pioneering US-Indian Services company to serve major global automotive OEMs (GM, Ford, Nissan, Peugeot) from India-based delivery centers in the early 2000s
Acquired by Wipro (NYSE: WIT)
Former Wipro, EDS Chief Executive
Founded Creative Synergies Group In 2011
Locations: Headquartered in the U.S., multiple delivery centers in India (Bengaluru, Pune, Noida), branch offices in Germany, U.K, Netherlands and Japan
Culture: Creative has a flat organization and an agile culture of positivity, entrepreneurial spirit, customer centricity, teamwork, and meritocracy
Creative Synergies Group 3 Year Vision
Continue Business Growth of 30-40% per annum
Establish AI/ML Technology Services Leadership in Our Target Verticals
Niche Technology Acquisitions in the U.S. / Europe
Job Title:
Azure Data Engineer Lead/Architect
Experience:
10+ years
Job Summary:
We are seeking a skilled and motivated Azure Data Engineer Lead/Architect with strong relevant experience. Candidate will play a pivotal role in designing, implementing, and optimizing large-scale data solutions on the Microsoft Azure platform. Candidate will work closely with other cross-functional teams to ensure data solutions are scalable, secure, and high-performance. The ideal candidate will have a strong background in data engineering, deep expertise in Azure Databricks and proven leadership skills to guide and mentor the team.
Key Responsibilities:
Architect and Design Data Solutions:
Lead the design and implementation of scalable, secure and high-performing data solutions on Azure, ensuring alignment with business goals and technical requirements.
Data Pipeline Development:
Build and optimize end-to-end data pipelines to collect, process and analyze data from various sources using Azure Databricks, Azure Data Factory and other Azure data services.
Cloud Infrastructure Management:
Architect and maintain cloud data infrastructure using Azure Data Lake, Azure Synapse Analytics, Azure SQL Data Warehouse and Azure Blob Storage.
Collaborate with Cross-functional Teams:
Work closely with data architects, business analysts and developers to gather requirements, define data models and ensure smooth integration of data across systems.
Design and build scalable data pipelines to support AI/ML use cases, including feature engineering, model training datasets, and real-time inference workflows using Azure-native services.
Collaborate with Data Scientists and ML Engineers to product ionize machine learning models by implementing robust data workflows, feature stores, model monitoring pipelines, and MLOps best practices on…
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