Ashish Mehta
Data Engineer @BMO
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WORK HISTORY
Data Engineer @BMO
Designed and maintained scalable Azure Data Factory pipelines, automating end-to-end data integration workflows for financial systems.• Configured ADF activities like Copy Data, Execute SQL, and Data Flow to extract data from Azure SQL Database and on-premises sources.• Built and optimized Spark jobs and Databricks notebooks for complex data transformations, aggregations, and machine learning tasks.• Developed T-SQL scripts and stored procedures in Azure Synapse Analytics, improving query performance and resource utilization.• Integrated Azure Databricks with Data Lake Storage Gen2 to create efficient pipelines for big data analytics and ETL workflows.• Implemented Delta Lake on Databricks for ACID transactions, data versioning, and scalable Lakehouse architecture.• Configured Unity Catalog for centralized data governance, lineage tracking, and fine-grained access control.• Ensured data security and compliance with Azure Key Vault, meeting standards like PCI DSS and GDPR.• Leveraged Snowflake to load and transform data from multiple sources, using SQL and variant data types for complex transformations.• Utilized Python for ETL tasks, extracting and processing data from databases, APIs, and flat files.• Set up Azure Monitor and Log Analytics for monitoring pipelines, databases, and virtual machines.• Created and maintained documentation and knowledge base articles in Confluence, supporting team collaboration and knowledge sharing.
EDUCATION
Vancouver Island University
Computer Science
Chitkara University
Bachelor of Engineering - BE
ABOUT ASHISH MEHTA
I’m a Data Engineer who loves turning messy, complex data into reliable, actionable insights. Over the past 5+ years, I’ve built and optimized scalable data pipelines, real-time streaming systems, and cloud-based analytics platforms across Azure, AWS, and Databricks.At Bank of Montreal, I improved data processing efficiency by 40% and led a migration from on-premises to the cloud, making data more accessible and cost-effective. At Konica Minolta, I modernized legacy ETL workflows with Airflow and PySpark, improving accuracy and scalability. Earlier at Hopper, I built pipelines and dashboards that empowered teams with faster, smarter decision-making.What drives me is helping businesses unlock the true value of their data—whether that’s reducing processing times, enabling real-time analytics, or ensuring data quality at scale.Outside of work, I enjoy exploring the latest cloud innovations, mentoring peers, and staying curious about how data can shape the future.
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