Strategy & Analytics
AI & Data
In this age of disruption, organizations need to navigate the future with confidence, embracing decision making with clear, data-driven choices that deliver enterprise value in a dynamic business environment.
The AI & Data team leverages the power of data, analytics, robotics, science and cognitive technologies to uncover hidden relationships from vast troves of data, generate insights, and inform decision-making. Together with the Strategy practice, our Strategy & Analytics portfolio helps clients transform their business by architecting organizational intelligence programs and differentiated strategies to win in their chosen markets.
AI & Data will work with our clients to:
- Implement large-scale data ecosystems including data management, governance and the integration of structured and unstructured data to generate insights leveraging cloud-based platforms
- Leverage automation, cognitive and science-based techniques to manage data, predict scenarios and prescribe actions
- Drive operational efficiency by maintaining their data ecosystems, sourcing analytics expertise and providing As-a-Service offerings for continuous insights and improvements
Experience:
6+ years of hands-on experience in designing and developing conceptual, logical, and physical data models for relational, dimensional, and NoSQL data platforms.
Knowledge of Data Vault, NoSQL, Dimensional Modeling, Graph data model, and proficiency in at least one of these.
Proven experience with data warehousing, data lakes, and enterprise big data platforms.
Knowledge of databases such as columnar databases, vector databases, graph databases, etc.
Strong knowledge of metadata management, data modeling, and related tools (e.g., Erwin, ER/Studio).
Experience with ETL tools and data ingestion protocols.
Familiarity with cloud-based data warehousing solutions (e.g., Google BigQuery, AWS Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
Experience in creating comprehensive documentation of data models, data dictionaries, and metadata.
Preferred Qualifications:
Experience with cloud modernization projects and modern database technologies.
Certification in data modeling or database design.
Strong communication and presentation skills.
Good to Have Qualifications:
Experience in creating data models that comply with data governance policies and regulatory requirements.
Experience leading initiatives to modernize data platforms using cloud-based solutions such as Google BigQuery, AWS Redshift, Snowflake, etc.