Sharp Decisions

Senior Data Analyst

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Analyst in Charlotte, NC, with a contract length of unspecified duration. Pay rate is $40-$45/hr. Candidates must have 6+ years of experience in data analysis within banking/financial services, and proficiency in GCP, BigQuery, SQL, and Python.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
360
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πŸ—“οΈ - Date
December 19, 2025
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Phoenix, OR
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🧠 - Skills detailed
#Physical Data Model #Data Warehouse #Data Mart #Forecasting #Data Analysis #Spark (Apache Spark) #"ETL (Extract #Transform #Load)" #SQL (Structured Query Language) #GCP (Google Cloud Platform) #Snowflake #Computer Science #Data Engineering #EDW (Enterprise Data Warehouse) #Python #JSON (JavaScript Object Notation) #BigQuery #Data Quality #Compliance #BI (Business Intelligence)
Role description
We are Hiring Sr. Data Analyst in Charlotte NC for our direct client. Need Local Folks only. Experience with BANKING/FINANCIAL SERVICES CLIENTS IS MANDATORY. Pay range - $40-$45/hr Required Skills:- β€’ Bachelors or Master's degree in Computer Science, Data Engineering, Information Systems, or related field. β€’ 6+ years of experience in data analysis, modeling, and supporting complex data ecosystems. β€’ Hands-on experience with GCP, BigQuery, SQL, and Python. β€’ Proficiency in SQL, Spark, and ETL/ELT processes. β€’ Familiarity with JSON and semi-structured data handling. Understanding retail banking data flows and regulatory requirements. β€’ Strong problem-solving skills and ability to communicate insights to technical and non-technical audiences. Key Responsibilities β€’ Perform advanced data analysis, including trend identification, forecasting, and segmentation. β€’ Design and maintain logical and physical data models aligned with business requirements and compliance standards. β€’ Apply strong knowledge of data warehousing principles, including Fact and Dimension tables, Star and Snowflake schema modeling. β€’ Manage structured and semi-structured data formats (e.g., JSON). β€’ Gather and document data requirements for building enterprise data warehouses, data marts, and BI solutions. β€’ Collaborate with product managers and stakeholders to define KPIs, metrics, and reporting standards. β€’ Ensure data quality, lineage, and maintain an organizational data glossary across all assets. β€’ Document requirements for data models, pipelines, and ETL/ELT processes.