Jobs via Dice
Senior Data Analyst
Location: Charlotte, NC | Employment: Full-time | Seniority Level: Mid‑Senior level
We are hiring a Senior Data Analyst for our direct client. Local candidates only.
Experience with banking/financial services clients is mandatory.
Hourly Pay: $40–$45/hr | Approx. Annual Salary: $90,000–$132,000
Key Responsibilities
Perform advanced data analysis, including trend identification, forecasting, and segmentation.
Design and maintain logical and physical data models aligned with business requirements and compliance standards.
Apply strong knowledge of data warehousing principles, including Fact and Dimension tables, Star and Snowflake schema modeling.
Manage structured and semi‑structured data formats (e.g., JSON).
Gather and document data requirements for building enterprise data warehouses, data marts, and BI solutions.
Collaborate with product managers and stakeholders to define KPIs, metrics, and reporting standards.
Ensure data quality, lineage, and maintain an organizational data glossary across all assets.
Document requirements for data models, pipelines, and ETL/ELT processes.
Qualifications & Skills
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
6+ years of experience in data analysis, modeling, and supporting complex data ecosystems.
Hands‑on experience with Google Cloud Platform, BigQuery, SQL, and Python.
Proficiency in SQL, Spark, and ETL/ELT processes.
Familiarity with JSON and semi‑structured data handling.
Understanding of retail banking data flows and regulatory requirements.
Strong problem‑solving skills and ability to communicate insights to technical and non‑technical audiences.
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We are hiring a Senior Data Analyst for our direct client. Local candidates only.
Experience with banking/financial services clients is mandatory.
Hourly Pay: $40–$45/hr | Approx. Annual Salary: $90,000–$132,000
Key Responsibilities
Perform advanced data analysis, including trend identification, forecasting, and segmentation.
Design and maintain logical and physical data models aligned with business requirements and compliance standards.
Apply strong knowledge of data warehousing principles, including Fact and Dimension tables, Star and Snowflake schema modeling.
Manage structured and semi‑structured data formats (e.g., JSON).
Gather and document data requirements for building enterprise data warehouses, data marts, and BI solutions.
Collaborate with product managers and stakeholders to define KPIs, metrics, and reporting standards.
Ensure data quality, lineage, and maintain an organizational data glossary across all assets.
Document requirements for data models, pipelines, and ETL/ELT processes.
Qualifications & Skills
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
6+ years of experience in data analysis, modeling, and supporting complex data ecosystems.
Hands‑on experience with Google Cloud Platform, BigQuery, SQL, and Python.
Proficiency in SQL, Spark, and ETL/ELT processes.
Familiarity with JSON and semi‑structured data handling.
Understanding of retail banking data flows and regulatory requirements.
Strong problem‑solving skills and ability to communicate insights to technical and non‑technical audiences.
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