Overview
Skills
Job Details
Hi,
Please find the below job description and if you're interested please share your updated resume for reference.
Role: Technical Business Analyst
Location: Dallas, TX (Hybrid)
Business Domain: Financial Services, Private Equity, Asset Management, Commercial Real Estate and/or Commercial Credit experience preferred
Technical Business Analyst
Education:
Bachelor's degree in Computer Science, Information Technology, Business Administration, or a related field.
Advanced certifications in data analytics and business analysis are a plus.
Technical Skills:
Data Warehouse Expertise:
In-depth knowledge of data warehouse core concepts, including data architecture, data integration, and data governance.
Strong understanding of logical data modeling and relational database design.
Query Writing:
Proficiency in writing SQL queries for data extraction, analysis, and reporting.
Azure Services:
Experience working with Azure cloud services, including (preferred but not
mandatory):
Azure SQL Server
Azure Data Factory (ADF)
Azure Databricks.
Tools & Technologies:
Familiarity with ETL tools like SSIS.
Exposure to data visualization tools such as Power BI or Tableau.
Industry Knowledge:
Prior experience in the financial industry is a strong advantage, with knowledge
of financial data structures and reporting requirements.
Soft Skills:
Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
Excellent communication and interpersonal skills to collaborate effectively with technical teams and business stakeholders.
Ability to work independently and manage multiple priorities in a fast-paced environment.
Attention to detail and a commitment to delivering high-quality work.
Responsibilities:
1. Requirements Gathering:
Collaborate with business stakeholders to gather and document requirements for data engineering projects.
Translate business needs into technical specifications for data pipelines, data models, and reporting solutions.
Data Analysis:
Analyze large datasets to identify trends, patterns, and insights that support business decision-making.
Write and optimize SQL queries to extract and manipulate data for analysis.
3. Data Modelling:
Design and maintain logical data models to support data warehouse architecture and reporting needs.
4. Collaboration with Data Engineers:
Work closely with senior and junior data engineers to ensure data pipelines and ETL processes align with business requirements.
Provide input on database schema design and optimization.
5. Azure Services Utilization:
Leverage Azure cloud services to support data integration, storage, and analytics workflows.
Collaborate on projects involving Azure Data Factory, Azure SQL Server, and Databricks.
6. Documentation:
Create and maintain comprehensive documentation for business requirements, data models, and technical workflows.
7. Financial Industry Insights:
Apply knowledge of financial data structures and reporting standards to ensure compliance and accuracy in data solutions.
8. Technology Evaluation:
Stay updated with emerging technologies and best practices in data analysis and business intelligence.
Recommend new tools and technologies to improve efficiency and scalability.