aditya's CV
aditya nair
Senior Data Engineer | Azure Databricks | PySpark | Data Platforms
Profile summary
Accomplished Senior Data Engineer with 4 years of progressive experience in data engineering, platform development, and ETL pipeline architecture. Multilingual professional fluent in 4 languages with a strong track record of designing Azure Databricks data platforms, migrating Spark workloads, and optimizing data warehouse performance. Committed to building scalable data systems and automated validation frameworks that deliver governed datasets for analytics and artificial intelligence applications.
Career highlights
Azure Databricks and Data Platforms: Architects and maintains Azure Databricks data platforms, delivering governed datasets for analytics, AI, and reporting applications while establishing automated validation frameworks.
ETL Migration and Pipeline Development: Managed data engineering functions, overseeing the migration of Spark ETL workloads, the development of scalable REST APIs using Python, and the delivery of end-to-end data pipeline orchestration.
Performance Optimization and Delta Lake: Optimized Snowflake and Azure Synapse data models, improving query performance by 30 percent and implementing Bronze, Silver, and Gold Delta Lake architecture.
Professional Certification: Holds the IBM Data Science Professional Certificate along with certifications in Python and Elasticsearch.
Key skills
Professional experience
Directs data platform engineering initiatives, focusing on Azure Databricks architecture, automated validation frameworks, and enterprise-grade data governance. Manages the delivery of governed datasets for AI systems, analytics, and reporting applications while establishing coding standards, reusable frameworks, and metadata-driven ingestion pipelines across development environments.
- Architects and maintains Azure Databricks data platforms delivering governed datasets for analytics, AI, and reporting applications.
- Defines data testing strategies and automated validation across Bronze, Silver, and Gold layers.
- Engineers CI/CD data quality gates covering schema, nulls, duplicates, integrity, freshness, volumes, and reconciliation.
- Develops GenAI and AI-agent workflows for automotive assembly instructions using governed engineering data and business rules.
- Builds MCP-based integration layers enabling standardized and governed AI-agent access to enterprise data.
Managed data engineering functions within the technology group, overseeing the migration of Spark ETL workloads, the development of scalable REST APIs using FastAPI and Python, and the delivery of end-to-end data pipeline orchestration through Apache Airflow DAGs across varied enterprise data environments.
- Optimized Snowflake and Azure Synapse data models, improving query performance by 30% and implementing SCD Type 2 for historical data management.
- Enhanced Azure Data Factory integration pipelines across APIs, databases, JSON, and CSV sources, improving integration efficiency by 20%.
- Implemented Bronze, Silver, and Gold Delta Lake architecture, improving data retrieval performance by 30% and enabling scalable data processing.
Projects
Developed an AI-ready enterprise data platform enabling governed GenAI and agentic workflow, automated validation, and scalable data processing.
Built a high-volume real-time data pipeline focused on reliable streaming, automated data quality, and optimized processing performance.
Developed a scalable serverless data platform for automated ingestion, transformation, monitoring, and recovery across diverse data sources.
Education
Information Technology
Electronics and Communication Engineering
Certifications
Languages
English · Professional
Hindi · Professional
Malayalam · Professional
Tamil · Professional