Wajid Jafri

- Split an old 3 TB Aurora MySQL problematic cluster with 40 databases into three newer, smaller, manageable sets using a near-zero downtime strategy with Data Migration (DMS).
- Created a content delivery website using real-time automation with an HTTP API, Lambda Function, Dynamodb table, SES, CI/CD and global CloudFront edge locations.
- Set up real-time data sync between RDS SQL Server 2019 and RDS Oracle 19c using Data Migration Service (DMS).
- Generated reports using AWS QUICKINSIGHTS using an 11 GB dataset of customer data.
- Set up API authorization methods using Lambda function and Cognito user pools.
- Created an AWS Document-DB cluster with two readers and one writer instance with EC2 access.
- Moved EC2 MySQL databases with DMS to an RDS cluster with Standby and Read Replicas.
- Reduced expenses by creating on-demand serverless Amazon Aurora RDS DEV instances.
- Set up zero-downtime migration using DMS full load with a change data capture (CDC).
- Created DEV and QA using Production Amazon RDS MySQL database manual snapshots
- Created new RDS MySQL databases from manual snapshots using Cloud Formation Stacks using Parameters to hide admin credentials and enforce the use of SSL.
- Supported Oracle Cloud Fusion & ERP applications (SaaS /PaaS / OIC) technology to drive simplification and reusability.
- Added 2TB storage to an Oracle Cloud Infrastructure (OCI) database to the DATA disk group.
- Optimized Oracle OCI 19c database long-running queries using COE, Indexes, and SQL Profiles.
- Trace the most repeated SQLs in the OEM past 30-day Snapshots on an OCI database and tune them, which provided a 50% reduction in the database time.
- Installed OEM 13.5 with host agents on Oracle OCI Cloud. Set up database and host alert notification system.
- Tuned Top 30 recurring SQLs in AWR snapshots. Assigned best execution plans with COE SQL Profiles, cutting runtime from 20+ mins to seconds.
- Wrote Lambda Functions in Python 3.6 to send emails for the stop and start of EC2s.
- Loaded JSON & CSV data in DynamoDB when uploaded to an S3 using Lambda Python Functions.
- Created new IAM Policies and Roles for CloudWatch Logs and SNS with Topic and Subscriptions.
- Set up new DynamoDB tables with primary keys. Performed batch-write operations on them with Python scripts. Utilized Boto3 documentation for syntax.
- Created new sources like S3, EC2, and DynamoDB tables using Boto3 in Python scripts.
- Pulled specific data from huge CSV files stored in S3 using S3Object SQL statements with Boto3.
- Created multiple APIs using Python Lambda functions to query and update DynamoDB tables.
- Migrated on-premises online Oracle databases to OCI with Zero Downtime Migration (ZDM).
- Analyzed and compared images using AWS Reckognition facial recognition service.
- Created Ansible Playbooks to automate a fleet of server configurations and checks.
- Predicted college admissions using Sagemaker Canvas using training and test data sets.
- Created a Stock app with Kinesis Data Firehose, which stored data in an S3 bucket. Then used Athena tables on S3 to generate analytic reports.
- Created an ECS Fargate Serverless cluster with NGINX webserver containers from ECR. A public IP address provides user connections.
- Moved application containers from ECS Fargate to AWS App Runner with auto deployments from the Git repository.
- Spin up an AWS Kubernetes cluster with one master and two worker nodes. Pod containers serve a Docker image. KOPS and KUBECTL were installed on an EC2.
Environment: Oracle 11g-19c, RAC, MS SQL Server 2019, Terraform, Jira, Amazon Cloud, Oracle Cloud, Azure Cloud, Oracle Fusion & ERP applications, Python, Github, Ansible

- Built a new two-node Oracle 18c RAC Cluster Production database with Physical Standby.
- Provided the performance tuning of slow-running queries in the Production Murex application.
- Installed a new Oracle 13c Enterprise Manager Cloud Control for database monitoring.
- Implemented OEM 13c Alert Email System. It monitors databases, clusters, hosts, etc.
- Set up database VMs with Data Guard Compute nodes in Oracle Cloud Virtual Cloud Network.
- Loaded data in an Autonomous Database using Oracle Cloud's Object Storage service.
- Benchmark testing of Amazon EC2 servers in a VPC cloud for Oracle and SQL Server workloads.
- Helped new application developers use the Postgres database in the Azure Cloud.
- Created an MS SQL Server 2014 two-node failover cluster with two Window nodes.
- Set up Always-On Availability Groups and scheduled SQL Server 2014 backups with encryption.
Environment: Oracle 18c, MS SQL Server 2014, RAC, Github, Python, Terraform, PostgreSQL, OEM, AWS

- Supporting Ellucian Banner 9 ERP Applications with Oracle 11g databases for Admission, HR, etc.
- Upgraded Banner 8 application to Banner 9 along with database upgrade.
- Created new Physical Standby databases for disaster recovery. Created documentation.
- Configured Alert-Email system for databases and host monitoring using OEM 13c.
- Wrote scripts to start and shut down the databases, listeners, and OEM Agents with scripts.
- Cloned databases using RMAN DUPLICATE. It is required for migration to new hardware.
- Applied the latest Security Patches to the databases, OEM 13c OMS, Agents, and Plugins.
- Configured daily online backups for databases using Cloud Control. Supported Museum App.
- Upgraded Museum application with the database 11g to 12c and OS from Linux 6 to Linux 7.
- Installed and configured MS SQL Server 2014 in development, QA, and Production
Environment: Oracle 18c/12c, Standby Databases, Data Guard, OEM, Banner 9, SQL Server 2014, Github