Assct Spclst, Data Analytics Professional

24 months as Consultant

10+ years of hands-on experience delivering BI and analytics solutions in enterprise or consulting environments. - Strong banking or financial services domain experience (risk, finance, operations, client reporting, etc.). - Expert-level SQL skills advanced joins, CTEs, window functions, aggregations, and performance tuning. - Hands-on knowledge of Python for analytics / ML and AI use cases. - Strong proficiency in Microsoft Power BI, including DAX, Power Query (M), semantic modeling, and visualization best practices. - Experience with Direct Query sources such as Snowflake, Azure SQL, or Synapse Analytics. - Solid understanding of Power BI Service artifacts (datasets, dataflows, gateways, RLS, deployment pipelines). - Understanding of security models relevant to banking: RBAC concepts, least privilege, auditability, and sensitive data handling. - Working knowledge of Microsoft Fabric concepts and modern analytics architectures. - Ability to work independently as a technical lead, solve ambiguous problems, and own solutions end-to-end. - Strong communication skills ability to engage effectively with both technical and non-technical stakeholders. - Experience supporting self-service BI models and governed analytics patterns. - Knowledge of prompt and context engineering (preferably in PBI Copilot). As an experienced data analytics resource at NTAM, you will be responsible for supporting key analytics initiatives with a focus on delivering robust, scalable, and user-centric Business Intelligence and data science solutions. You will work closely with architects, data engineers, and business stakeholders to design and develop enterprise-grade reports, dashboards, semantic models, and predictive models. Additionally, you will perform advanced SQL-based data preparation and optimization, while applying data engineering and AI/ML techniques to enhance insights. Responsibilities:

Design and develop Power BI reports, dashboards, and executive scorecards aligned with business and regulatory requirements. - Lead the design, build, and optimization of semantic models (tabular) using best practice data modeling and efficient DAX measures. - Write, debug, and tune advanced SQL queries across platforms such as Snowflake, Azure SQL, or other enterprise data stores. - Help drive AI-driven insights generation and advanced analytics using Machine Learning techniques. - Implement and optimize Direct Query and hybrid models, focusing on performance, query folding, and scalability. - Collaborate with solution architects, data engineers, analysts, and business users to gather requirements and deliver end-to-end analytics solutions. - Apply working knowledge of data engineering and AI/ML (Python/R or similar) for targeted use cases such as forecasting, anomaly detection, and segmentation. - Support Power BI service operations, including workspace manageme