The Data Warehouse Analyst job description

A Data Warehouse Analyst is a data professional responsible for designing, developing, maintaining, and analyzing data stored in a data warehouse—a centralized repository used to store large volumes of structured data from different sources for reporting and analysis.

Key Responsibilities:

  1. Data Modeling & Design:
    • Develop and maintain data models (e.g., star schema, snowflake schema).
    • Define the structure of tables, relationships, and indexing strategies.
  2. ETL Development:
    • Design and implement ETL (Extract, Transform, Load) processes to move data from various sources (e.g., databases, applications, APIs) into the data warehouse.
    • Ensure data quality, consistency, and integrity during transformation.
  3. Data Integration:
    • Integrate data from different systems like ERP, CRM, and other business applications.
  4. Reporting & Analysis:
    • Work with BI tools (like Power BI, Tableau, or Looker) to create dashboards and reports.
    • Analyze data to identify trends, insights, and performance metrics.
  5. Performance Tuning:
    • Optimize queries, indexes, and storage to ensure fast and efficient data retrieval.
  6. Collaboration:
    • Work closely with data engineers, business analysts, data scientists, and stakeholders to understand data needs and deliver solutions.
  7. Data Governance & Security:
    • Ensure compliance with data privacy laws and internal data policies.
    • Implement access control and auditing for the data warehouse environment.

Common Tools & Technologies:

Skills Needed:

  • Strong SQL and database design skills.
  • Knowledge of data warehousing concepts (e.g., OLAP, ETL, normalization/denormalization).
  • Familiarity with cloud data platforms (e.g., AWS, Azure, GCP).
  • Analytical thinking and attention to detail.
  • Ability to translate business requirements into data solutions.

Typical Background:

  • Degree in Computer Science, Information Systems, or a related field.
  • Experience in data analysis, business intelligence, or software development.

Can you create a sample job description for a Data Warehouse Analyst?

Here is a sample job description for a Data Warehouse Analyst role.

You can customize it based on your organization’s specific needs:

Job Title: Data Warehouse Analyst

Location: [City, State or Remote]

Department: Data & Analytics / IT

Reports to: Data Engineering Manager / Director of Analytics

Employment Type: Full-time

Job Summary:

We are seeking a highly skilled and detail-oriented Data Warehouse Analyst to join our Data & Analytics team.

The ideal candidate will be responsible for designing, developing, and maintaining our enterprise data warehouse systems and supporting business users with data access, reporting, and analytical needs.

Key Responsibilities:

  • Design and implement scalable data warehouse solutions to support business intelligence and reporting needs.
  • Develop and manage ETL pipelines to extract data from various sources, transform it, and load it into the data warehouse.
  • Create and maintain data models (star/snowflake schema) and dimensional data structures.
  • Monitor data integrity and quality across data sources and warehouse.
  • Work with business analysts and stakeholders to understand data requirements and deliver meaningful insights.
  • Develop ad-hoc and scheduled reports using BI tools (e.g., Power BI, Tableau).
  • Optimize SQL queries and improve data warehouse performance.
  • Maintain documentation for data models, ETL processes, and reporting logic.
  • Ensure security and compliance with data governance policies.

Qualifications:

Required:

  • Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or a related field.
  • 3+ years of experience in data warehousing, data analysis, or BI development.
  • Strong experience with SQL and relational databases (e.g., SQL Server, PostgreSQL, Oracle).
  • Proficiency in ETL tools (e.g., Informatica, Talend, Azure Data Factory, SSIS).
  • Experience with data modeling and dimensional modeling techniques.
  • Familiarity with BI reporting tools (e.g., Power BI, Tableau, Looker).

Preferred:

  • Experience with cloud platforms such as AWS Redshift, Google BigQuery, or Azure Synapse.
  • Knowledge of scripting languages (e.g., Python, Shell).
  • Familiarity with data governance, privacy, and compliance standards (e.g., GDPR, HIPAA).

Soft Skills:

  • Strong analytical and problem-solving skills
  • Excellent communication and collaboration abilities
  • Detail-oriented and quality-focused
  • Ability to manage multiple projects and deadlines.

Benefits:

  • Competitive salary and performance bonuses.
  • Health, dental, and vision insurance.
  • 401(k) with company match.
  • Remote work flexibility.
  • Learning and development opportunities.