Job Description & How to Apply Below
Required Skills &
Qualifications:
5+ years of relevant experience in data science and analytics, preferably in Financial Services
Experience in leading and managing data analytics teams.
Hands-on expertise in data engineering (SQL, Python) and BI development (Tableau, Power
BI etc.) with a focus on data analysis and modelling.
Experience with deploying data analytics and ETL/BI solutions within cloud ecosystems like Amazon Web Services, Google Cloud Platform, Microsoft Azure
Experience with financial datasets and strong mathematical background.
Exposure to financial metrics datasets and asset classes.
Strong communication skills, both written and oral, with a business and financial aptitude.
Key Responsibilities:
Lead a range of BI and data analytics projects and POCs for financial services clients.
Lead the design and development of advanced analytics solutions using Microsoft Fabric and Power BI.
Architecting and managing Azure Data Factory pipelines to streamline data processing and integration for analytics and reporting into BI tools like Power BI and Tableau.
Develop and deploy data integration solutions, including data ingestion, transformation, and delivery to consumers within Microsoft Fabric, while utilizing optimal storage formats and layers.
Design and implement scalable and efficient data pipelines for both structured and unstructured data from diverse sources using Microsoft Fabric technologies (Dataflow gen2, Data Pipelines, PySpark notebooks, Spark SQL, and Python)
Optimize BI solutions for performance and scalability.
Create and maintain comprehensive documentation covering Data Fabric architecture, processes, and procedures.
Serve as the primary contact for client communications, ensuring clear and effective information exchange.
Incorporate feedback from clients and continuously improve models, dashboards, and processes.
Maintain project documentation, including technical specifications, user guides, and project progress reports
Key Responsibilities
Preferred
Qualification:
Master's in science or engineering disciplines such as Computer Science, Engineering, Mathematics, Physics, etc.
Preferred - Professional certifications on tools/technologies listed above
Microsoft Certified:
Power BI Data Analyst Associate
Databricks Certified Data Engineer
Snowflake Snow Pro Core Certification
Tableau Desktop Specialist
Optional:
Financial Modeling & Valuation Analyst (FMVA) for finance domain depth
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