Abhinand Saravanan

I’m a results-driven Senior Data Engineer with 8+ years of total IT experience specializing in Azure Data Engineering, AWS Data Engineering, and Big Data Engineering. I’m Certified Databricks Data Engineer Professional and a Microsoft Fabric/Azure Data Engineering credential holder, and I focus on building scalable data architectures that turn complexity into reliable, actionable insights.

I spearheaded end-to-end ETL delivery using Azure Data Factory (ADF), Azure Databricks and Native Databricks on AWS, Azure Synapse, and Snowflake, with governed ingestion and transformation across enterprise systems. I engineered cloud migrations to ADLS Gen2 and Amazon S3 using Medallion architecture (Raw, Bronze, Silver, Gold) to improve integrity, security, compliance, and structured storage. I also orchestrated large-scale automation integrating RDBMS, SFTP/FTP, and APIs, enabling advanced transformations with PySpark and Spark SQL.

To ensure data trust at scale, I designed an automated data profiling framework in Databricks that extracts metadata attributes like cardinality, null checks, distinct values, min/max statistics, and schema-level profiling metrics. I built reusable profiling pipelines for single-table, full-schema, and recently altered top-table profiling, with standardized CSV outputs and datatype-specific validation logic. I also led CI/CD and deployments using Databricks workflow YAML, GitHub PRs, and promoted workflows across DEV/UAT/QA/PROD.

I’ve driven measurable performance improvements—up to 30% runtime reduction—and helped modernize platforms by migrating to open table formats using Delta Lake and Apache Iceberg. Today, I’m extending that approach into Microsoft Fabric (OneLake, Lakehouse, Data Factory, Spark-based engineering) and building self-service BI layers with Tableau and Power BI, partnering closely with data scientists, product teams, and business stakeholders on data contracts, SLAs, and quality standards.