Suresh K

Senior Data Engineer with 7+ years of experience designing, building, and optimizing cloud-native data platforms using Snowflake and AWS. Specialized in ETL/ELT modernization, SQL performance optimization, Change Data Capture (CDC), cloud automation, and enterprise Data Governance. Proven track record of improving analytical query performance, modernizing legacy data pipelines, optimizing Snowflake compute costs, and delivering scalable, secure, and high-performance analytics solutions.

Strong expertise in Python, SQL, production engineering, and Agile software delivery.

Senior Consultant — Data Engineering - EXL Service - Bengaluru, India

(2019-08)

Progressed through multiple engineering roles delivering enterprise-scale cloud data platforms, governance solutions, and Snowflake modernization initiatives across the insurance domain.

Senior Snowflake Data Engineer - EXL Service - Bengaluru, India

(2023-06)

• Designed and implemented an end-to-end Snowflake Medallion Architecture, orchestrating data ingestion into Bronze, standardized transformations in Silver, and business-ready Gold data marts using SCD Type 1 and Type 2 modeling principles.
• Optimized performance of enterprise Snowflake workloads, reducing analytical query execution time by approximately 70% through advanced SQL tuning, warehouse optimization, and execution plan improvements.
• Designed and maintained 12 production Snowflake Streams & Tasks pipelines, enabling reliable Change Data Capture (CDC) processing with automated monitoring, error logging, and operational alerting.
• Modernized 6 high-frequency ETL pipelines by implementing Snowflake Dynamic Tables, simplifying orchestration, improving maintainability, and reducing operational overhead.
• Reduced Snowflake compute consumption by approximately 180 credits per month by replacing scheduled Materialized View refreshes with Dynamic Tables, eliminating dedicated refresh warehouses.
• Engineered scalable semi-structured data pipelines using VARIANT, FLATTEN, and LATERAL JOIN, transforming deeply nested JSON payloads (up to 6 levels) into curated analytical datasets powering 15 Tableau dashboards.
• Reduced archival storage costs by approximately 35% by implementing Snowflake Iceberg Tables, enabling shared data access across Snowflake, Spark, and Amazon Athena without data duplication.
• Standardized enterprise data transformations by developing reusable Snowflake Stored Procedures and modular SQL components, improving maintainability and consistency across reporting pipelines.
• Automated enterprise reporting workflows using Snowflake, Python, AWS Lambda, and Amazon S3, reducing manual effort through automated validation, reconciliation, and secure file delivery.
• Strengthened enterprise data security by implementing Snowflake Masking Policies to enforce role-based access for sensitive PII data.
• Accelerated development and testing cycles by leveraging Zero-Copy Cloning to provision Development and UAT environments in under 3 minutes, replacing time-consuming database refresh activities.
• Improved production resilience by utilizing Snowflake Time Travel to rapidly restore critical datasets following accidental data modifications.
• Provided technical leadership by mentoring junior engineers, conducting code reviews, and promoting best practices for Snowflake development, SQL optimization, and production support.
• Partnered with architects, product owners, QA teams, and business stakeholders to drive technical design discussions, sprint planning, estimation, and successful production releases across multiple business domains.

Data Governance Engineer - EXL Service - Bengaluru, India

(2022-08 - 2023-06)

• Improved enterprise data discoverability and regulatory compliance by implementing Informatica Axon and Enterprise Data Catalog (EDC) across business-critical datasets.
• Established end-to-end metadata management and enterprise data lineage, enabling improved impact analysis, governance, and traceability.
• Standardized business glossary and stewardship processes, improving metadata quality and governance adoption across cross-functional teams.
• Collaborated with business and technical stakeholders to strengthen enterprise governance processes and data management practices.

AWS Data Engineer - EXL Service - Bengaluru, India

(2019-10 - 2022-08)

• Designed and developed scalable ETL pipelines using AWS Glue, PySpark, SQL, and Amazon S3 supporting enterprise reporting and analytical workloads.
• Built cloud-native ingestion frameworks capable of processing structured and semi-structured datasets for downstream analytical platforms.
• Improved batch processing performance by optimizing SQL transformation logic and ETL workflows across enterprise data pipelines.
• Standardized data ingestion and transformation by developing reusable ETL components and validation frameworks, improving data quality and operational consistency.
• Maintained production reliability by supporting deployments, incident resolution, root cause analysis, and operational troubleshooting.
• Collaborated with cross-functional teams to translate business requirements into scalable cloud data engineering solutions following Agile development practices.

Bachelor of Engineering - Computer Science - New Horizon College of Engineering (2019)