Senior Associate, Azure Data Engineer, Data and Analytics Advisory, Pan India
Job Description
- Azure
- Google Cloud
- Accepting Feedback
- Active Listening
- Agile Scalability
- Amazon Web Services (AWS)
- Analytical Thinking
- Apache Airflow
- Apache Hadoop
- Azure Data Factory
- Communication
- Creativity
- Data Anonymization
- Data Architecture
- Database Administration
- Database Management System (DBMS)
- Database Optimization
- Database Security Best Practices
- Databricks Unified Data Analytics Platform
- Data Engineering Platforms
- Data Infrastructure
- Data Integration
- Data Lake
- Data Modeling
- Data Pipeline
- Lead the development and deployment of AIML/generative AI models, managing full project lifecycles from conception to delivery.
- Collaborate with senior stakeholders to identify strategic opportunities for AI applications, aligning them with business objectives.
- Collaborate/Oversee teams of data scientists and engineers, providing guidance, mentorship, and ensuring high-quality deliverables.
- Drive research and innovation in AI techniques and tools, fostering an environment of continuous improvement and learning.
- Ensure compliance with data governance standards and ethical AI practices in all implementations.
- Present AI insights and project progress to clients and internal leadership, adapting technical language to suit audience expertise levels.
- Inclusive benefits
- Flexibility programmes
- Mentorship
- Support for wellbeing
Line of Service
Advisory
Industry/Sector
Not Applicable
Specialism
Data, Analytics & AI
Management Level
Senior Associate
Job Description & Summary
Our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
In data engineering, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
Responsibilities:
Key Responsibilities:
- Lead the development and deployment of AIML/generative AI models, managing full project lifecycles from conception to delivery.
- Collaborate with senior stakeholders to identify strategic opportunities for AI applications, aligning them with business objectives.
- Collaborate/Oversee teams of data scientists and engineers, providing guidance, mentorship, and ensuring high-quality deliverables.
- Drive research and innovation in AI techniques and tools, fostering an environment of continuous improvement and learning.
- Ensure compliance with data governance standards and ethical AI practices in all implementations.
- Present AI insights and project progress to clients and internal leadership, adapting technical language to suit audience expertise levels.
Mandatory skill sets:
AI/ML, NLP, and Generative AI models
Preferred skill sets:
Azure, Google Cloud
Years of experience required:
3-5 Years
Education qualification:
Advanced degree (Master’s or Ph.D.) in Computer Science, Artificial Intelligence, Data Science, or related discipline.
Education
Degrees/Field of Study required: Bachelor Degree, Master Degree
Required Skills
Data Engineering
Optional Skills
Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline
