Sameer uddin

Developed and optimized data pipelines in Azure using Databricks and Spark
Integrated data from Oracle APIs into Delta Lake with Medallion Architecture
Reduced pipeline processing time by 50% through performance tuning
Utilized Azure Blob Storage and Delta Tables for scalable data storage
Collaborated with analytics teams to deliver clean, accessible datasets
Working with multiple clients to optimize and streamline complex and fragmented data pipeline processes

Developed new ETL workflows to handle growing data volumes, helping reduce processing time and system load
Migrated several batch jobs to near real-time data pipelines, enhancing data availability for downstream applications
Supported and guided junior engineers through code reviews, technical sessions, and pair programming to improve team efficiency
Proactively identified and resolved infrastructure-level issues, contributing to improved system stability and uptime
Worked with junior team members to optimize legacy pipelines, resulting in more efficient resource usage and easier maintenance
Investigated and fixed data quality issues from production systems, helping ensure accurate and timely reporting
Collaborated closely with product teams to align data engineering efforts with evolving product features and priorities

Developed new ETL workflows to handle growing data volumes, helping reduce processing time and system load., Migrated several batch jobs to near real-time data pipelines, enhancing data availability for downstream applications., Supported and guided junior engineers through code reviews, technical sessions, and pair programming to improve team efficiency., Proactively identified and resolved infrastructure-level issues, contributing to improved system stability and uptime., Worked with junior team members to optimize legacy pipelines, resulting in more efficient resource usage and easier maintenance., Investigated and fixed data quality issues from production systems, helping ensure accurate and timely reporting., Collaborated closely with product teams to align data engineering efforts with evolving product features and priorities.

Collaborating with The Fertility Partners, a leading organization in the North American and Canadian medical industry, focusing on advanced fertility treatments
Partner with senior team members to manage and optimize ETL pipelines, ensuring efficient data flow and integration
Utilize AWS Glue for the creation and ongoing monitoring of robust data pipelines
Employ AWS Athena to efficiently retrieve and compile data for reporting purposes
With the help of Terraform, design, optimize and manage data pipeline architectures to ensure robust and scalable infrastructure
Conduct data scraping to collect comprehensive profiles of fertility doctors across various regions in Canada
Consolidate this information into DynamoDB to create a centralized data repository

Collaborating with 'The Fertility Partners,' a leading organization in the North American and Canadian medical industry, focusing on advanced fertility treatments., Partner with senior team members to manage and optimize ETL pipelines, ensuring efficient data flow and integration., Utilize AWS Glue for the creation and ongoing monitoring of robust data pipelines., Employ AWS Athena to efficiently retrieve and compile data for reporting purposes., With the help of Terraform, design, optimize and manage data pipeline architectures to ensure robust and scalable infrastructure., Conduct data scraping to collect comprehensive profiles of fertility doctors across various regions in Canada. Consolidate this information into DynamoDB to create a centralized data repository. This strategic aggregation supports enhanced targeted marketing and facilitates more effective schedule management for hospitals.

Extract large and complex data from client’s data sources by performing ETL process
Filter and clean data using multiple tools to prepare financial reports via automation
Find useful and actionable information in large data sets
Identifying and communicating financial data discrepancies to client and senior management
Closely work with team lead to develop and implement data collection systems, data analytics and other strategies to optimize workflow
Dealt with high influx of projects by setting and adjusting priorities
Coach other less experienced colleagues and provide them with on-the-job training
Perform basic General ledger reconciliations

Extract large and complex data from client’s data sources by performing ETL process., Filter and clean data using multiple tools to prepare financial reports via automation., Find useful, and actionable information in large data sets., Identifying and communicating financial data discrepancies to client and senior management., Closely work with team lead to Develop and implement data collection systems, data analytics and other strategies to optimize workflow., Dealt with high influx of projects by setting and adjusting priorities., Coach other less experienced colleagues provide them with on-the-job training., Perform basic General ledger reconciliations.

Use SQL for fetching large and complex data from database for analytical reporting
Make and optimize SQL queries for monthly, weekly and adhoc reporting
Make dashboard on Power BI for yearly and quarterly audit reports where they can analyze audit department's quarterly and yearly performances

Use SQL for fetching large and complex Data from Database for Analytical Reporting., Make and optimize SQL Queries for Monthly, Weekly and adhoc reporting., Make Dashboard on Power BI for Yearly and Quarterly Audit reports where they can analyze Audit department's Quarterly and yearly performances.

Developed and optimized data pipelines in Azure using Databricks and Spark, Integrated data from Oracle APIs into Delta Lake with Medallion Architecture, Reduced pipeline processing time by 50% through performance tuning, Utilized Azure Blob Storage and Delta Tables for scalable data storage, Collaborated with analytics teams to deliver clean, accessible datasets, Working with multiple clients to optimize and streamline complex and fragmented data pipeline processes.

Design and implement ETL pipelines, sourcing data from multiple origins to staging areas, enhancing data availability for analytical reporting and BI dashboards
Conduct thorough diagnostics to identify and resolve flaws in data pipelines, optimizing them for scalability and improved performance
Designed and implemented 8+ ETL pipelines using Python and SQL, enhancing data availability for reporting and BI dashboards
Designing and developing an ERD model for the database and building a Data Warehouse layer on top of the gold layer to support business stakeholders and reporting needs
Integrated incremental loading techniques, reducing resource consumption by 80% and improving synchronization speed by 30%
Implemented an ETL logging system, reducing bug resolution time by 50% compared to the previous approach
Executed data migration from PostgreSQL to MS SQL Server, improving access management and system integration

Design and implement ETL pipelines, sourcing data from multiple origins to staging areas, enhancing data availability for analytical reporting and BI dashboards., Conduct thorough diagnostics to identify and resolve flaws in data pipelines, optimizing them for scalability and improved performance., Designed and implemented 8+ ETL pipelines using Python and SQL, enhancing data availability for reporting and BI dashboards., Designing and developing an ERD model for our database and building a Data Warehouse layer on top of our gold layer to support business stakeholders and reporting needs (Moving towards dimensional modeling)., Integrated incremental loading techniques, reducing resource consumption by 80% and improving synchronization speed by 30%., Implemented an ETL logging system, reducing bug resolution time by 50% compared to the previous approach., Executed data migration from PostgreSQL to MS SQL Server, improving access management and system integration.