Key Skills
Strong understanding of data concepts, including data warehousing, data mining, data quality, and data governance.
Familiarity with AI/ML concepts, algorithms, and applications (e.g., machine learning, deep learning, natural language processing). Client Handling and Communication, Problem Solving, Systems thinking, Passion of technology, Adaptability, Agility, Analytical thinking, Collaboration
Skills and attributes for success
- 15-17 years of total experience with 10+ years in Data Strategy and architecture field
- 15-17 years of total experience with 7+ years in AI Strategy & implementation.
- Strong knowledge of data architecture, data models and cutover strategies using industry standard tools and technologies
- Architecture design and implementation experience with medium to complex on-prem to cloud migrations with any of the major cloud platforms (preferably AWS/Azure/GCP)
- Solid hands-on 10+ years of professional experience with creation and implementation of data science engagements and helping create AI/ML products
- Proven track record of implementing machine-learning solutions, development in multiple languages and statistical analysis
- 7+ years experience in Azure database offerings [ Relational, NoSQL, Datawarehouse ]
- 7+ years hands-on experience in various Azure services preferred Azure Data Factory, Kafka, Azure Data Explorer, Storage, Azure Data Lake, Azure Synapse Analytics, Azure Analysis Services & Databricks
- Minimum of 8 years of hands-on database design, modeling and integration experience with relational data sources, such as SQL Server databases, Oracle/MySQL, Azure SQL and Azure Synapse
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
- Strong creative instincts related to data analysis and visualization.
- Aggressive curiosity to learn the business methodology, data model and user personas.
- Strong understanding of BI and DWH best practices, analysis, visualization, and latest trends.
- Experience with the software development lifecycle (SDLC) and principles of product development such as installation, upgrade and namespace management
- Willingness to mentor team members
- Solid analytical, technical and problem-solving skills
- Excellent written and verbal communication skills
- Strong project and people management skills with experience in serving global clients
To qualify for the role, you must have
- Master s Degree in Computer Science, Business Administration or equivalent work experience.
- Fact driven and analytically minded with excellent attention to details
- Hands-on experience with data engineering tasks such as building analytical data records and experience manipulating and analysing large volumes of data
- Relevant work experience of minimum 15 to 17 years in a big 4 or technology/ consulting set up
- Help incubate new finance analytic products by executing Pilot, Proof of Concept projects to establish capabilities and credibility with users and clients. This may entail working either as an independent SME or as part of a larger team
