Data Analyst

Key Responsibilities
Current State Discovery
Collaborate with business and technical stakeholders to understand the existing data landscape.
Conduct a Current State Discovery process, reviewing existing data sources, formats, and systems to identify data gaps, redundancies, and inconsistencies.
Document the current data architecture and workflows to establish a baseline for future improvements.
2Data Harmonization
Standardize and harmonize disparate data sources to create a unified, consistent dataset across the organization.
Work with the source team to identify key data elements and ensure they are aligned across multiple systems, reducing discrepancies and improving data quality.
Develop and apply data transformation rules for seamless integration across various systems.
Data Modeling
Design and implement data models to support the organizations reporting, analysis, and business intelligence needs.
Build logical and physical data models, ensuring that they support clean, efficient, and accurate reporting and analytics.
Collaborate with database administrators, data engineers, and other stakeholders to ensure models are optimized for performance and scalability.
4Source to Target (S2T) Mapping for Future State:
Lead the Source to Target (S2T) Mapping process, working closely with the source team to define how data will be mapped from its original systems (source) to the future state (target) environment.
Create comprehensive S2T mapping documentation to define data transformation, data lineage, and data flow for various business processes.
Ensure that all mapped data complies with the organizations standards for data accuracy, completeness, and consistency Required Skills & Qualifications:
Education: Bachelors degree in Data Science, Statistics, Computer Science, Engineering, Business Analytics, or a related field.
Experience:
6years of experience as a Data Analyst, Data Modeler, or in a similar data-related role.
Experience with data harmonization, data modeling, and S2T mapping.
Strong familiarity with data transformation processes and tools.
Technical Skills:
Proficiency in SQL, Excel, and Python (Pandas, NumPy).
Experience with data visualization tools (e.g., Tableau, Power BI, Google Data Studio).
Experience with data modeling tools (e.g., Erwin, PowerDesigner).
Knowledge of ETL processes, data integration, and cloud based data environments (AWS, Google Cloud, Azure)
Analytical Skills: Ability to analyze large datasets, identify patterns, and create meaningful insights.
Knowledge on Finance Planning & Allocations, Risk Analysis (finance and insurance domain)
Communication Skills: Strong ability to document processes and communicate data findings to both technical and non-technical stakeholders.
Teamwork Proven ability to work collaboratively with cross functional teams, especially the source team Preferred Qualifications:
Knowledge of data governance and data quality frameworks.
Experience with machine learning or predictive analytics.
Familiarity with big data technologies (e.g., Hadoop, Spark) and data warehousing concepts.
Certifications in data analysis, data modeling, or business intelligence (e.g., Certified Data Management Professional (CDMP), Microsoft Certified Data Analyst Associate).