Overview
Hybrid
Depends on Experience
Full Time
Skills
Data Analysis
SQL
Azure SQL
Azure Data Factory
Data Lake
Blob Storage
Tableau
Python
Microsoft Power BI
Databricks
Job Details
Data Analyst/Data SME
Location- Client location preference in Memphis, TN. Hybrid
Job Description:
We are seeking a skilled and detail-oriented Data Analyst / SME with experience in the banking domain to support enterprise data analysis, reporting, and data mapping initiatives. The ideal candidate should possess strong analytical capabilities, hands-on experience querying and interpreting data, and proficiency in mapping data across systems in a cloud-based environment. This role requires working knowledge of Microsoft Azure data services, and experience with Databricks is a strong plus.
Responsibilities and Qualifications:
- Minimum 8+ years of experience as a Data Analyst or Data SME, with strong exposure to banking and financial services.
- Proven expertise in data analysis, data profiling, and data validation across large-scale datasets.
- Proficient in writing complex SQL queries to extract, join, filter, and aggregate data from relational databases like SQL Server or Azure SQL. Skilled in using window functions and optimizing queries for large datasets to support accurate and efficient reporting and analysis..
- Strong in developing data mapping documents, tracing data flow from source to destination systems.
- Experience working with Azure Data Services including Azure SQL, Azure Data Factory, Data Lake, and Blob Storage.
- Hands-on experience or good understanding of Databricks for data transformation, data exploration, and processing.
- Ability to generate meaningful reports and dashboards to support business stakeholders and regulatory requirements.
- Familiarity with banking data structures, products (e.g., deposits, loans, payments), and reporting standards.
- Detail-oriented with excellent problem-solving skills and ability to work with cross-functional teams including business, data engineering, and QA.
- Strong communication and documentation skills to clearly articulate findings and recommendations to technical and non-technical stakeholders.
- Familiarity with data governance, lineage, and quality best practices is preferred.
- Experience with BI tools (e.g., Power BI, Tableau) and scripting languages (e.g., Python, PySpark) is a plus.
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