Job Title: Data Warehouse Supervisor
Job Summary:
We are seeking a Data Warehouse Supervisor to lead and oversee the development, implementation, and optimization of enterprise data warehouse (EDW) solutions. The ideal candidate should have strong SQL expertise, data modeling skills, ETL experience, and cloud-based data warehouse knowledge, along with the ability to manage and mentor a team of data warehouse analysts and engineers. This role requires technical leadership, project management, and collaboration with cross-functional teams to support business intelligence (BI) and data analytics initiatives.
Key Responsibilities:
- Supervise and lead a team of data warehouse analysts and engineers, ensuring best practices and project success
- Oversee the design, implementation, and maintenance of enterprise data warehouse solutions
- Manage data integration, ETL workflows, and pipeline automation to ensure data consistency and accuracy
- Optimize SQL queries, indexing, partitioning, and caching strategies for high-performance analytics
- Ensure data governance, security, and compliance with industry regulations (GDPR, HIPAA, PCI-DSS, CCPA)
- Collaborate with business units, IT teams, and executives to define data requirements and reporting needs
- Monitor and troubleshoot data warehouse performance issues, implementing optimizations where necessary
- Oversee cloud-based data warehouse migration projects (AWS Redshift, Google BigQuery, Snowflake, Azure Synapse)
- Develop and maintain OLAP cubes, data marts, and business intelligence (BI) solutions
- Lead ETL development, real-time streaming, and batch processing workflows
- Mentor junior team members, conduct training sessions, and enforce data warehouse best practices
- Stay updated on the latest trends in data warehousing, cloud computing, AI-driven analytics, and big data
Skills and Knowledge Required:
- Strong SQL expertise (SQL, PL/SQL, T-SQL) and experience in query optimization
- Deep understanding of data modeling (star schema, snowflake schema, fact & dimension tables)
- Proficiency in ETL tools (Apache NiFi, Talend, Informatica, SSIS, AWS Glue, Apache Airflow)
- Experience with cloud-based data warehousing platforms (AWS Redshift, Google BigQuery, Snowflake, Azure Synapse)
- Knowledge of business intelligence tools (Power BI, Tableau, Looker, QlikView) for reporting and visualization
- Familiarity with DevOps and CI/CD for data warehouse automation (Terraform, Kubernetes, Docker, Git)
- Experience in big data processing (Hadoop, Spark, Kafka, Flink) for real-time analytics
- Understanding of data security best practices, encryption techniques, and role-based access control (RBAC)
- Proficiency in Python, Bash, or PowerShell for data automation and workflow orchestration (optional)
Educational Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Information Technology, or a related field
- Certifications in Data Warehousing, SQL, Cloud Databases, or BI Tools (AWS Certified Data Analytics, Snowflake Certified Data Engineer, Google Professional Data Engineer) are a plus
Experience:
- 8+ years of experience in data warehousing, ETL development, and SQL optimization
- 2+ years of experience in a supervisory or leadership role, managing data teams and overseeing projects
- Proven ability to lead enterprise data warehouse initiatives and implement scalable solutions
Key Focus Areas:
- Data Warehouse Architecture & Optimization
- Cloud-Based & Scalable Data Warehousing Solutions
- ETL Pipeline Development & Data Integration Strategies
- Data Governance, Compliance & Security
- Leadership & Mentorship in Data Warehousing
Tools and Technologies:
- Databases: AWS Redshift, Google BigQuery, Snowflake, Azure Synapse, MySQL, PostgreSQL, Microsoft SQL Server, Oracle
- ETL & Data Pipeline Tools: Apache NiFi, Talend, Informatica, SSIS, Airflow, dbt
- BI & Reporting Tools: Power BI, Tableau, Looker, QlikView
- Big Data Technologies: Hadoop, Spark, Kafka, Flink, Databricks
- Version Control & DevOps: Git, Terraform, Kubernetes, Docker, Jenkins
Other Requirements:
- Strong leadership, decision-making, and project management skills
- Excellent communication skills to interact with stakeholders, executives, and development teams
- Ability to mentor junior team members and enforce best practices
- Passion for data-driven decision-making and enterprise data strategies