Our client is a rapidly growing, automation-led service provider specializing in IT, business process outsourcing (BPO), and consulting services. With a strong focus on digital transformation, cloud solutions, and AI-driven automation, they help businesses optimize operations and enhance customer experiences. Backed by a global workforce of over 32,000 employees, our client fosters a culture of innovation, collaboration, and continuous learning, making it an exciting environment for professionals looking to advance their careers.
Committed to excellence, our client serves 31 Fortune 500 companies across industries such as financial services, healthcare, and manufacturing. Their approach is driven by the Automate Everything, Cloudify Everything, and Transform Customer Experiences strategy, ensuring they stay ahead in an evolving digital landscape.
As a company that values growth and professional development, our client offers global career opportunities, a dynamic work environment, and exposure to high-impact projects. With 54 offices worldwide and a presence in 39 delivery centers across 28 countries, employees benefit from an international network of expertise and innovation. Their commitment to a 'customer success, first and always' philosophy ensures a rewarding and forward-thinking workplace for driven professionals.
We are currently searching for a Analytics Data science and IOT Engineer:
Responsibilities:
- Design and implement IoT data pipelinesusingAzure Data FactoryandDatabricks.
- Develop analytics modelsfor IoT sensor data to drive actionable insights.
- Build and optimize ETL processesfor large-scale IoT and analytics datasets.
- Collaborate with cross-functional teams tointegrate IoT solutionswith enterprise systems.
- Maintain documentation for data workflows, models, and IoT architectures.
Requirements:
- 4+ years of experienceindata science, IoT engineering, or related roles.
- Proficiency in Databricksfor data processing and analytics.
- Hands-on experience withAzure Data Factoryfor ETL and data integration.
- Strong understanding of IoT systems, sensor data, and real-time analytics.
- Familiarity with statistical modeling, machine learning, and data visualization tools.
Note:
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