Job Title: Senior Data Warehouse Analyst
Job Summary:
We are seeking a Senior Data Warehouse Analyst to lead the design, development, and optimization of enterprise data warehouse (EDW) solutions. The ideal candidate will have extensive experience in data architecture, ETL processes, SQL performance tuning, and cloud-based data warehouses. This role requires technical leadership, collaboration with cross-functional teams, and driving data governance and security for business intelligence and analytics initiatives.
Key Responsibilities:
- Architect, develop, and optimize large-scale data warehouse solutions for business intelligence and analytics
- Design and manage database schemas, including star and snowflake schemas, fact and dimension tables
- Develop and enhance ETL (Extract, Transform, Load) pipelines for data integration, transformation, and cleansing
- Optimize query performance, indexing strategies, partitioning, and execution plans for large datasets
- Ensure data governance, compliance, and security, including encryption, role-based access control (RBAC), and regulatory compliance (GDPR, HIPAA, PCI-DSS)
- Lead data warehouse migration to cloud-based platforms (AWS Redshift, Google BigQuery, Snowflake, Azure Synapse)
- Automate data pipeline workflows using orchestration tools such as Apache Airflow, AWS Glue, dbt
- Manage real-time data streaming and batch processing frameworks for high-speed analytics
- Develop and maintain OLAP cubes and data marts for business intelligence reporting
- Collaborate with business stakeholders, data engineers, analysts, and DevOps teams to define data strategies and best practices
- Monitor and troubleshoot data pipeline failures, query slowness, and data inconsistencies
- Mentor and lead junior data warehouse analysts, providing training and enforcing best practices
- Stay updated on modern data warehousing technologies, big data solutions, and machine learning integration
Skills and Knowledge Required:
- Expert proficiency in SQL, PL/SQL, T-SQL, and advanced query optimization techniques
- Extensive experience in data warehouse design, ETL pipelines, and data modeling
- Deep knowledge of cloud-based data warehouse platforms (AWS Redshift, Google BigQuery, Snowflake, Azure Synapse)
- Expertise in ETL tools and frameworks (Apache NiFi, Talend, Informatica, SSIS, Airflow)
- Strong experience with BI and reporting tools (Power BI, Tableau, Looker, QlikView)
- Knowledge of data pipeline automation, workflow orchestration, and DevOps integration
- Understanding of big data technologies (Hadoop, Spark, Kafka, Flink) for large-scale data processing
- Hands-on experience with scripting (Python, Bash, PowerShell) for data automation
- Strong data security and compliance knowledge, including encryption, access controls, and auditing
- Experience with data governance, metadata management, and data lineage tracking
Educational Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field
- Certifications in Data Warehousing, Cloud Databases, SQL, or BI Tools (AWS Certified Data Analytics, Snowflake Certified Data Engineer, Google Professional Data Engineer) are a plus
Experience:
- 5-8+ years of hands-on experience in data warehousing, ETL development, and SQL optimization
- Proven experience in leading enterprise data warehouse projects and managing large-scale datasets
Key Focus Areas:
- Advanced Data Warehouse Architecture & Optimization
- Cloud-Based Data Warehousing & Big Data Integration
- ETL Process Development & Performance Tuning
- Data Governance, Compliance, & Security Best Practices
- Business Intelligence & Analytics Enablement
Tools and Technologies:
- Databases: MySQL, PostgreSQL, Microsoft SQL Server, Oracle
- ETL & Data Pipeline Tools: Apache NiFi, Talend, Informatica, SSIS, Airflow, dbt
- Cloud Data Warehouses: AWS Redshift, Google BigQuery, Snowflake, Azure Synapse
- BI & Reporting Tools: Power BI, Tableau, Looker, QlikView
- Big Data & Streaming Technologies: Hadoop, Spark, Kafka, Flink
- Version Control & DevOps: Git, Terraform, Kubernetes, Docker
Other Requirements:
- Strong leadership, decision-making, and analytical skills
- Proven ability to mentor and lead data teams
- Excellent communication skills to interact with stakeholders, data engineers, and executives
- Passion for data-driven decision-making and optimizing enterprise data solutions