Zia Anwar

Strategic Technical Leadership & Snowflake Optimization Advanced Analytics & AI Innovation Cross-Functional Engineering

• Strategic Advisory & Performance Engineering: Serve as a strategic advisor to enterprise customers, optimizing complex SQL workloads to achieve significant reductions in compute costs and query latency.
• Platform Subject Matter Expertise: Act as the lead SME for core and emerging Snowflake features, including Dynamic Tables, Performance Tuning, and Snowflake PostgreSQL.
• High-Performance Architecture: Lead complex technical engagements to design and optimize high-performance Snowflake environments for Priority Support customers.
  Leveraged Materialized Views, Search Optimization, and Workload Tuning to eliminate bottlenecks and maximize platform value.
• Complex Workload Design: Design, review, and optimize SQL for analytical, transactional, and mixed workloads, providing expert data model recommendations and query tuning.
• Cloud Ecosystem Integration: Architect and deploy robust data pipelines across AWS and Azure, utilizing Airflow for orchestration and dbt for modular data transformation.
• Agentic AI & LLMs: Design and implement Agentic AI frameworks using Snowflake Cortex and Snowflake Intelligence to automate internal workflows and drive intelligent decision-making.
• AI/ML Automation: Develop end-to-end ML solutions and autonomous agents for internal projects, streamlining operations through predictive automation.
• Programmable Data Engineering: Build scalable, non-SQL data processing logic using Snowpark, Java, and Python, effectively reducing reliance on external compute clusters.
• Hybrid Data Solutions: Bridge legacy systems with modern cloud architecture using Spark and the Snowflake Connector for Python to ensure seamless data mobility and high-performance ingestion.

Advanced Data Engineering & Optimization AI, ML & Modern Development Core Impact Areas

• Dedicated Technical Leadership: Serve as a Staff Cloud Support Engineer for high-value Priority Support customers, acting as a trusted technical advisor and the primary escalation point for mission-critical issues.
• Strategic Collaboration: Partner with Support Account Managers, account teams, and Engineering on proactive reviews, complex escalations, and the development of long-term customer success plans.
• Engineering Liaison & SME: Act as a Subject Matter Expert (SME) for Performance and Dynamic Tables, collaborating directly with Engineering on deep-dive investigations, feature validation, and product roadmap improvements.
• Cross-Cloud Infrastructure: Support enterprise environments across AWS, GCP, and Azure, including the management of cloud-specific networking, security, and complex integration patterns.
• Real-Time Pipeline Architecture: Design, implement, and debug near-real-time pipelines using Dynamic Tables, Streams, and Tasks for incremental processing and orchestration.
• Performance & Cost Governance: Optimize storage and compute efficiency by implementing Auto Clustering, Search Optimization, and Materialized Views to balance performance with cost-efficiency.
• Business Continuity: Implement and troubleshoot Replication and Failover patterns to meet strict RPO/RTO and Disaster Recovery (DR) objectives across diverse regions and cloud providers.
• Advanced SQL & Modeling: Design and review complex SQL for analytical, transactional, and mixed workloads, providing expert query tuning and data model architecture recommendations.
• AI/ML Operationalization: Support advanced Cortex LLM and Machine Learning use cases, including model training, evaluation, and production-level operationalization on Snowflake.
• Programmable Data Solutions: Build and troubleshoot data pipelines and applications using Snowpark, Python, Java, and Spark, including the development of UDFs and stored procedures.
• DevOps & Automation: Contribute to CI/CD practices for Snowflake, focusing on Infrastructure-as-Code (IaC), deployment automation, and robust testing strategies.
• Technical Escalations: Resolving multi-layered issues spanning data, compute, and security under time-critical, high-pressure conditions.
• Internal Product Development: Developing internal tools and solutions using Python and Java to streamline support operations.
• Strategic Optimization: Transforming underperforming environments into high-efficiency Snowflake instances through proactive architectural reviews.

Database Administration & BI Architecture

• Strategic Customer Advisory: Served as the recognized Subject Matter Expert (SME) for performance and workload optimization for a portfolio of global strategic accounts, including Unilever, Capital One UK, SAMA Bank (Saudi Arabia), Target, and Etisalat.
• Workload Management & Governance: Designed and tuned complex Workload Management (TASM) rules and priority schedulers to balance high concurrency, protect critical SLAs, and prevent resource-draining runaway queries.
• SQL & Physical Design Optimization: Led large-scale performance tuning initiatives, optimizing physical database design through advanced indexing (PPI, MLPI), statistics collection strategies, and partitioning to reduce SLA breaches.
• Infrastructure Evolution: Orchestrated multiple high-impact database upgrades and platform migrations, ensuring zero-downtime transitions for mission-critical Enterprise Data Warehouses (EDW).
• Mission-Critical Incident Response: Investigated and resolved Tier-1 platform incidents, including complex query failures, batch processing bottlenecks, and resource contention under 24x7 operational models.
• Full-Stack Teradata DBA: Managed end-to-end administration tasks, including capacity planning, multi-petabyte space management, security (user/role) design, and robust backup/restore (BAR) strategies.
• BI & Semantic Layer Optimization: Partnered with BI teams to enhance Power BI, Tableau, and MicroStrategy performance by optimizing semantic models, underlying data structures, and query patterns.
• Operational Automation: Developed a suite of Linux shell scripts and automation tools to streamline system monitoring, health checks, and incident response routines.
• Hybrid Ecosystem Integration: Administered and integrated Big Data/Hadoop ecosystems and utilized Spark for distributed data processing alongside traditional RDBMS.