Ajayan V

Data Engineer with 4 years of experience building scalable data pipelines, ETL/ELT workflows, and cloud-based data platforms. Expert in Python, SQL, PySpark, and Azure (ADF, Databricks) with strong experience in data modeling, performance optimization, and large-scale data processing. Proven ability to design reliable data architectures, improve pipeline efficiency, and enable analytics and BI solutions using modern engineering practices including CI/CD, Git, and containerization.

Familiar with streaming pipelines, big data technologies, and ML-driven data applications.

CONSULTANT at SYNITI (2025-03 – 2025-12)

• Built ETL pipelines using PySpark, Spark SQL, and Python to process large volumes of retail transactional data, including sales, orders, inventory, and customer activity.
• Implemented Medallion architecture (Bronze, Silver, Gold layers) for scalable Data Lakehouse solutions.
• Wrote and optimized complex SQL/Spark SQL queries using joins, CTEs, subqueries, and window functions.
• Implemented batch data processing pipelines with support for full loads, incremental loads, and basic Change Data Capture (CDC) strategies.
• Migrated legacy data to cloud platforms with validation and reconciliation checks.
• Executed SQL-based data quality checks to validate retail metrics such as daily sales totals, inventory levels, and order completeness, ensuring high data accuracy for analytics teams.
• Implemented CI/CD pipelines using Azure DevOps and Git for automated deployment, version control, and environment management of data pipelines.
• Collaborated with cross-functional teams, stakeholders, and business users to translate data requirements into scalable data pipeline solutions.

TECHNOLOGY ANALYST at INFOSYS LIMITED (2019-03 – 2022-12)

• Developed modular Python ETL scripts to support batch and real-time data extraction, transformation, and loading workflows.
• Designed and integrated end-to-end ETL/ELT pipelines in Azure Data Factory to ingest and process data across Azure Data Lake, Azure SQL Database, and Azure Blob Storage.
• Developed and optimized Snowflake schemas (star/snowflake) for efficient querying and reporting.
• Implemented role-based access control (RBAC) in Snowflake by creating and managing custom roles aligned with organizational access policies.
• Utilized Spark SQL in Databricks to optimize data querying and improve analysis efficiency and query response times.
• Monitored and troubleshot PySpark and Databricks jobs using Spark UI and logs, identifying performance bottlenecks and implementing optimizations.
• Built familiarity with real-time streaming pipelines using Apache Kafka for continuous data ingestion.
• Applied data quality checks and supported Data Visualization - Power BI dashboards, reducing reporting errors by 20% and enabling better decision-making

MSc in MASTERS IN ADVANCED COMPUTER SCIENCE WITH DATA SCIENCE – UNIVERSITY OF STRATHCLYDE, GLASGOW, UNITED KINGDOM (2023-01 – 2024-03)

BTech in BACHELORS IN ELECTRONICS AND COMMUNICATION ENGINEERING – UNIVERSITY OF CALICUT, KERALA, INDIA (2014-06 – 2018-06)