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Data Analyst

Data Analyst

PeopleCaddie

Chicago, IL • Remote

$80 - $85/hr

Other

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Job description

Job Description:
Title: Senior Data Analyst / Data Modeler - Contract
Client: Large Public Accounting Firm
Engagement: 6+ Month Contract
Work Model: Fully Remote
Rate: $80-$85/hour (C2C)
Role Overview
The Senior Data Analyst / Data Modeler serves as a hands-on technical resource responsible for designing, implementing, and supporting enterprise data models and data warehouse solutions. This role focuses on translating business and analytical requirements into scalable logical and physical data models that support reporting, analytics, and performance measurement across the organization.
Key Responsibilities
  1. Design, plan, and document logical and physical enterprise relational data models.
  2. Translate logical designs into physical database structures and define end-to-end data flows.
  3. Implement and maintain physical data models on cloud platforms such as Snowflake.
  4. Partner with business users to gather data requirements and define KPIs and performance metrics.
  5. Develop source-to-target mapping documents, including business transformation rules.
  6. Perform data profiling and data quality analysis to ensure integrity, accuracy, and consistency.
  7. Support QA and User Acceptance Testing (UAT) and provide ongoing production support for the enterprise data warehouse.
  8. Identify data issues, perform root-cause analysis, and implement corrective actions.
  9. Support data governance initiatives through monitoring, validation, and data quality controls.
  10. Collaborate effectively across development, architecture, data integration, and BI teams.
Required Experience & Qualifications
  1. Bachelor's degree in Computer Science, Information Systems, or equivalent professional experience.
  2. 7-10+ years of overall IT experience in data engineering, data analysis, or software development roles.
  3. 5-7 years of hands-on data analysis and modeling experience, including complex relational data models.
  4. 3-5 years of strong Snowflake experience with advanced SQL development.
  5. Proficiency with SQL and Python for data manipulation and analysis.
  6. Experience with BI and analytics tools such as Power BI, SAP BO, or Excel.
  7. Strong understanding of data warehousing concepts, data marts, and analytical database environments.
  8. Ability to create data flow diagrams and process documentation.
  9. Excellent analytical, problem-solving, and communication skills.
  10. Ability to work independently while collaborating across cross-functional teams in a dynamic environment.
Preferred Skills
  1. Experience in professional services, consulting, or client-facing technology roles.
  2. Familiarity with BI methodologies, OLAP tools, and enterprise analytics environments.
  3. Strong business acumen with the ability to communicate data architecture concepts to non-technical stakeholders.
  4. Comfort working in ambiguous or rapidly changing environments.

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Frequently asked questions

Q: What skills or qualities help someone succeed as a Data Analyst?

A: To succeed as a Data Analyst, key technical skills include proficiency in programming languages such as Python or R, expertise in data visualization tools like Tableau or Power BI, and knowledge of statistical analysis and machine learning concepts. Additionally, strong soft skills like effective communication, problem-solving, and collaboration are crucial for presenting insights to stakeholders and working with cross-functional teams. By combining these technical and soft skills, Data Analysts can drive business decisions, identify areas for improvement, and contribute to the growth and success of their organization.

Q: What is the career path for a Data Analyst?

A: A Data Analyst's typical career progression involves starting as an Entry-Level Data Analyst, where they collect, analyze, and interpret data to inform business decisions. As they gain experience, they can move into Mid-Level roles such as Senior Data Analyst or Business Analyst, where they take on more complex projects and lead smaller teams. Ultimately, they can advance to Senior Leadership positions like Data Scientist, Data Manager, or even Director of Analytics, where they oversee large-scale data initiatives and drive strategic business growth.\n\nKey opportunities for skill development and professional growth in this role include learning programming languages like Python or R, mastering data visualization tools like Tableau or Power BI, and staying up-to-date with emerging trends in machine learning and artificial intelligence. Additionally, Data Analysts can develop soft skills like communication, project management, and leadership to excel in their roles.\n\nLong-term career prospects for Data Analysts are diverse, with potential directions including transitioning into related fields like Business Intelligence, Data Engineering, or even becoming a Product Manager, or pursuing advanced degrees in Data Science or related fields to further specialize in areas like machine learning or data engineering.

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