We are seeking an experienced data analytics resource to support company's key analytics initiatives with a strong focus on delivering robust, scalable, and user-centric Business Intelligence and data science solutions. This role will work closely with architects, data engineers, and business stakeholders to design and develop enterprise grade reports, dashboards, semantic models, and predictive models. This resource will also perform advanced SQL based data preparation and optimization, while applying data engineering and AI/ML techniques to enhance insights.
The role is primarily BI engineering focused, with data engineering and applied ML/AI responsibilities, and is designed for a senior individual contributor who can operate independently, own requirements end to end and provide technical leadership within a global delivery model.
This role is ideal for a hands-on resource who is strong in semantic modeling, performance optimization, and stakeholder engagement, and can adapt quickly across complex, multidomain analytics initiatives in the banking and financial services space. Prior Asset Management experience and a working knowledge of financial data will also be critical.
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 management, publishing artifacts, refresh strategies, and Row Level Security (RLS) implementation.
- Define and promote BI engineering standards, performance best practices, and documentation for consistent offshore delivery.
- Troubleshoot and resolve complex data, model, and report level issues.
- Provide guidance, knowledge transfer, and informal mentoring to junior BI developers as needed.
- Stay current with Power BI, Microsoft Fabric, and analytics platform advancements and recommend improvements.
Required Skills:
- 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 nontechnical stakeholders.
- Experience supporting self-service BI models and governed analytics patterns.
- Knowledge of prompt and context engineering (preferably in PBI copilot).
