Nayala Sadaf

The project focused on creating a customer support reporting system designed to offer insights into the performance of customer support. This includes metrics like response times, ticket resolution rates, and overall customer satisfaction. The system was developed to enhance the understanding and monitoring of key aspects related to customer support effectiveness.

Involved in full software development life cycle, Business requirements Analysis, Data Analysis, Logical database design, coding Testing, Implementing, and deploying to business users.
Validated and updated the load status column in the SQL MI by comparing the record counts that copied to the ADLS gen 2 storage as delta format.
If the record count does not match load status to be updated as FAILED.
Analyzed source data coming different sources like SQL server tables, XML files and flat files then transformed according to business rules using Informatica.
Hands on experience on Unified Data Analytics with Databricks, Databricks Workspace User Interface, Managing Databricks Notebooks, Delta Lake with Python, Delta Lake with Spark SQL.
Implemented and maintained Azure Data Factory (ADF) workflows, enhancing data integration processes, and ensuring data accuracy and timeliness.
Collaborated with cross-functional teams to design, develop, and deploy scalable and maintainable solutions on Azure Databricks.
Integrated C# components into the existing application architecture, streamlining operations and improving overall system performance.
Loaded the aggregated data onto Oracle from Hadoop environment using Sqoop for reporting on the dashboard.
Developed and maintained SQL queries and stored procedures for efficient data retrieval and manipulation.
Actively participated in the planning and execution of Azure Function Apps, automating various tasks and improving system efficiency.
Demonstrated adaptability by seamlessly transitioning between different technologies based on project requirements.
Optimized performance of complex stored procedures by creating Clustered and Non-Clustered Indexes on tables.
Performed data quality issue analysis using SQL by building analytical warehouse on snowflake.
Created Pipeline in ADF using Linked services, Datasets, Pipeline to ETL data from different sources like Azure SQL, Blob storage, Azure SQL data warehouse, write-back tool.
Performance tuning of Spark applications for setting right batch interval time.
Developed JSON scripts for deploying the pipeline in Azure Data Factory that processes the data using SQL activity.
Used spark and Spark-SQL to read the parquets data and create the tables in hive using Scala API.
Work with team to design, build, automate and document a multi-tiered managed services platform.
Provided technical recommendations for installation and implementation of virtual environments.
Performed software and hardware upgrades, patches and reconfigurations on all virtual servers.
Work closely with our architects and engineers to recommend and design database or data storage solutions that effectively reflect the business needs, security, and service level.

Automation scripting ability (Bash/shell, Python).
Automated resulting scripts and workflow using Apache Airflow and shell scripting to ensure daily execution in production.
Worked on AWS Data Pipeline to configure data loads from S3 to Redshift.
Install and configure Apache Airflow for S3 bucket and Snowflake data warehouse and created dags to run the Airflow.
Exposure on Spark Architecture and how DD's work internally by involving and processing the data from Local files, HDFS and RDBMS sources by creating RDD and optimizing for performance.
Automated resulting scripts and workflow using Apache Airflow and shell scripting to ensure daily execution in production.
Installed and configured Hadoop Ecosystem like Hive, Oozie, Sqoop by which implemented using Cloudera Hadoop cluster for helping with performance tuning and monitoring.
Extract Transform and Load data from Sources Systems to AWS Data Storage services using Spark SQL.
Used Python to configure the services AWS glue, EC2, S3.
Used AWS Glue for data transformation, validate and data cleansing.
Wrote various data normalization jobs for new data ingested into Redshift.
Implemented Spark using Scala and spark SQL for faster testing and processing of data.
Created S3 buckets in the AWS environment to store files, sometimes which are required to serve static content for a web application.
Allotted permissions, policies and roles to users and groups using AWS Identity and Access Management (IAM).
Participate in the software development life cycle to ensure sound cloud solutions are implemented.
Experience with deployment and management of AWS services like EBS, EC2, S3, Lambda.

Involved in gathering business requirements, logical modelling, physical database, data sourcing and data transformation, data loading, SQL, and performance tuning.
Performed Data Analysis, Data Migration, Data Cleansing, Transformation, Integration, Data Import, and data export.
Processed data in Azure services including Azure Data Warehouse, Azure Data Storage, Azure Data Lake, Azure SQL, and Azure Databricks.
Loaded data into Azure SQL database from multiple sources using ETL pipelines created with Azure Data Factory, and stored credentials in Key Vaults for secure access.
Worked with Azure SQL Database Import and Export Service.
Involved in the entire process of BI application and information system development, including design, development, data analysis, business requirements gathering, user testing, and maintenance using MS SQL Server database management systems.
Monitored and addressed recurrent incidents and problems, identifying root causes, and escalating to the development team when necessary.
Developing data visualizations and dashboards with Python-based tools such as Matplotlib, Seaborn, and Bokeh.
Writing complex SQL queries and optimizing database performance using Python.
Designing and implementing data models using SSAS to support various data analysis needs.
Developing a project plan or roadmap that outlines the tasks and activities required to complete the project.
Troubleshooting and debugging data issues related to data quality, data flow, and performance optimization.
Provided managers with daily, weekly, and monthly reports that featured dynamic data and could be accessed anytime.
Optimized query performance by removing unnecessary columns, eliminating redundant and inconsistent data, normalizing tables, establishing joins, and creating clustered/non-clustered indexes wherever necessary.
Successfully created dynamic configuration packages in SSIS and used Event Handlers for Exception Handling in SSIS packages.
Created complex stored procedures for reporting services and defined report layouts in SSRS.
Debugged stored procedures and analyzed reports for any issues.
Configured SSIS packages with checkpoints, logging, error, and event handling to fix errors and redirect error rows.

Understanding present process flow and business functionalities and prepare ETL process flow for predictive analysis.
Provide day-to-day support to our partners, including but not limited to evaluating new channel or integration upgrades, handling troubleshooting requests.
Coordinated design reviews, ETL code reviews with teammates.
Performed tuned ETL code, Mappings, sessions, and databases.
Performed Unit, Integration and system testing of various jobs.
Created data maps in Informatica transformations.
Extensively worked with Informatica transformations.
Created technical documents for ETL process and design documents for each module.
Designed, developed, and supported ETL for data migration.
Performed Complex SSIS ETL operations to validate, cleanse, transform and load data to data warehouses.
Analyze each supply partner and find ways to optimize for better performance.
Developed Jobs in Talend Enterprise edition from stage to source, intermediate, conversion and Target.
Proficient in designing and developing SSIS packages for data extraction, transformation, and loading from heterogeneous data sources.
Experience in configuring and deploying SSIS packages to production environments.
Work closely with sales and account management teams to ensure successful delivery of advertising campaigns.
Proficient in working with various data sources like Flat files, Excel, Access, Oracle, and MySQL.
Experience in optimizing SQL Server performance by identifying and resolving performance bottlenecks.
Analyzed the requirements and framed the business logic for the EL process using Talend.
Developed business intelligence solutions using SQL server data tools versions and load data to SQL & Azure Cloud databases.
Worked on ETL Processes, Data mining, and Web reporting features for Data warehouses using Business Object.