Ajay Sai

Data Engineering professional with 3+ years of experience in designing, building, and optimizing enterprise-scale data warehousing solutions. Expertise in developing scalable, high-performance data pipelines using Snowflake, Cortex AI, Azure, and AWS cloud platforms. Skilled in data modelling, performance tuning, and implementing efficient cross-platform data integration to support advanced analytics and business intelligence.

Proven track record of delivering reliable, cost-efficient, and performance-optimized solutions in cloud-native environments.

Snowflake Developer - Hamsa IT Solutions Pvt Ltd

(2022-08)

Snowflake Developer - Telefonica

(2025-07)

• Designed and implemented end-to-end data ingestion pipelines to load raw data from AWS S3 into Snowflake using COPY INTO, custom file formats, and stage configurations.
• Configured and managed internal and external stages with optimised file formats (delimiter, null handling, header settings) for accurate and efficient bulk loading.
• Implemented error handling and data validation during ingestion using COPY options, enabling rejection tracking and improving upstream data quality.
• Automated batch and near real-time ingestion using Snowflake Tasks and Snowpipe, ensuring continuous data availability.
• Developed and maintained scalable dbt models to transform raw data into clean, enriched, and analytics-ready datasets using Staging → Intermediate → Mart architecture.
• Built complex SQL transformations using CTEs, window functions, and aggregations to support reporting and analytics requirements.
• Enforced data quality using dbt tests (not_null, unique, relationships, accepted_values) across all transformation layers.
• Created and maintained dbt documentation and lineage, improving visibility and traceability across pipelines.
• Optimised performance using incremental models, reducing processing time and compute cost by processing only changed data.
• Implemented SCD Type 2 using dbt snapshots to maintain historical data tracking and consistency.
• Leveraged Snowflake Cortex AI functions (COMPLETE, SENTIMENT, SUMMARIZE, CLASSIFY_TEXT) to enrich datasets with AI-driven insights.
• Integrated Cortex AI into dbt pipelines for automated text analysis on semi-structured and unstructured data.
• Utilised Snowflake Cortex ML capabilities to build predictive features such as forecasting and anomaly detection within the data warehouse.

Snowflake Developer - STC Telecom

(2024-01 - 2025-06)

• Planned and executed end-to-end Teradata to Snowflake migration strategy, including timeline, resource planning, risk assessment, and mitigation.
• Analysed existing Teradata environment to identify data assets, database objects, and ETL workflows for migration readiness.
• Architected and deployed Snowflake environments (databases, schemas, virtual warehouses, stages) optimised for scalability, performance, and cost efficiency.
• Migrated Teradata objects (tables, views, stored procedures) using automated tools and custom SQL-based conversion frameworks.
• Designed and implemented scalable ETL/ELT pipelines to enable seamless data migration with minimal downtime.
• Optimised data pipelines leveraging Snowflake's elastic compute and cloud-native features to improve performance and reduce cost.
• Performed comprehensive data validation, reconciliation, and audit checks to ensure post-migration data accuracy and completeness.
• Implemented data quality frameworks to detect and resolve discrepancies, ensuring high data integrity.
• Monitored and optimised query performance and warehouse utilisation for efficient processing.
• Established RBAC and data governance policies to ensure secure and compliant data access.
• Utilised Zero-Copy Cloning to create production-like environments for development and testing without impacting live systems.
• Improved query performance using clustering keys, micro-partition pruning, and warehouse scaling strategies.
• Documented migration best practices, optimisation techniques, and design standards for long-term maintainability.
• Delivered training and knowledge transfer sessions to enable team adoption of Snowflake best practices.
• Provided post-migration support and monitoring, ensuring system stability and smooth business transition.

Snowflake Developer - Caterpillar

(2022-08 - 2023-12)

• Implemented advanced Snowflake features such as Data Sharing, Zero-Copy Cloning, and Time Travel to improve data reusability, testing efficiency, and disaster recovery readiness.
• Led and contributed to unit and integration testing, ensuring reliability, accuracy, and completeness of data pipelines and transformations.
• Promoted engineering best practices through clean code standards, version control, and peer code reviews, enhancing code quality and team productivity.
• Collaborated with stakeholders by providing technical documentation, design discussions, and progress updates, ensuring alignment and transparency.
• Executed large-scale data ingestion from AWS S3 external stages into Snowflake using COPY INTO, handling both structured and semi-structured data (CSV, JSON).
• Managed data movement across local systems, internal stages, and Snowflake tables using commands such as PUT, GET, LIST, and COPY INTO.
• Designed and optimised a scalable Snowflake data warehouse architecture, balancing performance, scalability, and cost efficiency.
• Improved query performance using clustering keys, micro-partition pruning, and warehouse right-sizing strategies.
• Performed post-migration data validation and reconciliation, ensuring data accuracy, consistency, and completeness.
• Developed and implemented data quality frameworks to detect anomalies, resolve inconsistencies, and improve data reliability.
• Monitored and tuned query workloads using performance optimisation techniques, reducing execution time and improving system efficiency.
• Designed and optimised complex SQL queries, views, and materialised views to support high-performance reporting, analytics, and ETL workflows.
• Developed and executed data validation and cleansing routines, ensuring data accuracy, consistency, and integrity across systems.
• Contributed to database design and normalisation, creating ER diagrams and enforcing referential integrity for scalable schema development.
• Collaborated with stakeholders to translate business requirements into technical solutions, delivering efficient data models and database logic.
• Utilised Oracle SQL Developer for query development, debugging, and database object management across the SDLC.
• Supported data migration and transformation activities, including deployment, validation, and post-release monitoring across environments.

Masters - University of Leicester (2020)