Job Title: Mid-Level Data Warehouse Analyst
Job Summary:
We are seeking a Mid-Level Data Warehouse Analyst to design, develop, and optimize enterprise data warehouse (EDW) solutions. The ideal candidate should have strong SQL expertise, experience with ETL processes, data modeling skills, and hands-on experience with cloud-based data warehouses. This role involves managing large datasets, optimizing performance, ensuring data integrity, and collaborating with cross-functional teams to support business intelligence and analytics needs.
Key Responsibilities:
- Design and develop data warehouse architectures, including fact and dimension tables, star and snowflake schemas
- Optimize SQL queries, stored procedures, and indexing strategies for efficient data retrieval
- Develop and manage ETL (Extract, Transform, Load) pipelines for data ingestion and transformation
- Ensure data integrity, consistency, and governance across warehouse environments
- Monitor and troubleshoot database performance issues, slow queries, and data discrepancies
- Work with cloud-based data warehouses (AWS Redshift, Google BigQuery, Snowflake, Azure Synapse)
- Develop and maintain data marts and OLAP cubes for business intelligence reporting
- Collaborate with data engineers, analysts, and stakeholders to define data requirements and best practices
- Implement data security policies, role-based access control, and encryption for regulatory compliance
- Automate and schedule data warehouse jobs using workflow orchestration tools
- Stay updated on modern data warehousing technologies, big data trends, and best practices
Skills and Knowledge Required:
- Proficiency in SQL, PL/SQL, T-SQL, and query optimization techniques
- Experience in designing and managing data warehouses in MySQL, PostgreSQL, SQL Server, Oracle
- Hands-on experience with ETL tools (Apache NiFi, Talend, Informatica, SSIS, Airflow)
- Familiarity with cloud-based data warehouse platforms (AWS Redshift, Google BigQuery, Snowflake, Azure Synapse)
- Experience with BI and reporting tools (Power BI, Tableau, Looker) for visualization and analysis
- Knowledge of data pipeline automation and orchestration (Apache Airflow, AWS Glue, dbt)
- Understanding of database performance tuning, indexing, and partitioning techniques
- Experience in data governance, compliance, and security best practices
- Familiarity with scripting (Python, Bash, PowerShell) for automation (a plus)
- Strong analytical and problem-solving skills for handling large-scale data
Educational Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field
- Certifications in Data Warehousing, SQL, Cloud Databases, or BI Tools are a plus
Experience:
- 3-5 years of hands-on experience in data warehousing, ETL development, and SQL optimization
- Experience in handling high-volume data, real-time processing, and cloud-based analytics
Key Focus Areas:
- Data Warehouse Design & Optimization
- ETL Pipeline Development & Performance Tuning
- Cloud-Based Data Warehousing Solutions
- Data Governance, Security, and Compliance
- Business Intelligence & Reporting
Tools and Technologies:
- Databases: MySQL, PostgreSQL, Microsoft SQL Server, Oracle
- ETL & Data Pipeline Tools: Apache NiFi, Talend, Informatica, SSIS, Airflow
- Cloud Data Warehouses: AWS Redshift, Google BigQuery, Snowflake, Azure Synapse
- BI & Reporting Tools: Power BI, Tableau, Looker, QlikView
- Version Control & Automation: Git, Terraform, Ansible, Docker
- Monitoring & Performance Tools: SQL Profiler, SolarWinds, Prometheus, Grafana
Other Requirements:
- Strong ability to analyze data requirements and optimize warehouse performance
- Ability to mentor junior analysts and provide technical guidance
- Strong communication skills to collaborate with data engineers, software developers, and business stakeholders
- Passion for data-driven decision-making and scalable data warehouse solutions