Technical Business Data Analyst with Capital Markets - 12+ Yrs Experience

Overview

Hybrid
$100,000 - $120,000
Contract - W2
Contract - 12 Month(s)

Skills

Business Data
Analytical Skill
ADF
Attention To Detail
Business Intelligence
Capital Market
Cloud Computing
Collaboration
Business Analysis
Communication
Conflict Resolution
Data Integration
Data Visualization
Data Extraction
Data Warehouse Architecture
Data Engineering
Database
Database Design
Databricks
Data Warehouse
Data Analysis
Analytics
Data Architecture
Data Modeling
Data Structure
Data Governance
Decision-making
Documentation
Emerging Technologies
Extract
Transform
Load
Logical Data Model
Management
Microsoft Azure
Microsoft Power BI
Optimization
Problem Solving
Storage
Tableau
Requirements Elicitation
Technology Assessment
Specification Gathering
Regulatory Compliance
Finance
SQL Azure
Workflow
Soft Skills
Scalability
Writing
Reporting
SQL

Job Details

Job Description:

A senior (12+ years) Technical Business analyst with experience supporting Data Warehouse and Azure Data in a Capital Markets enterprise. Candidates need to have an excellent understanding of Data Warehouse process and the entire Azure Data suite as well as SQL and ETL.

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.
  2. 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 Modeling:
    • 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.
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