

Sharp Decisions
Senior Data Analyst
β - 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.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
360
-
ποΈ - Date
December 19, 2025
π - Duration
Unknown
-
ποΈ - Location
On-site
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π - Contract
Unknown
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π - Security
Unknown
-
π - Location detailed
Phoenix, OR
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π§ - 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.
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.






