Daris Salaam

About Daris Salaam

Passionate and results-driven Data Analytics and DevOps professional with hands-on…

Experience

1. Data Analyst Engineer

   IBM

   Sep 2022 — Present · Bengaluru, IN

   Cleaned and transformed large-scale raw datasets using Python (Pandas, NumPy) to improve data quality by 98.• Automated provisioning of AWS infrastructure using Terraform, enabling faster deployment of data pipelines and analytical environments.• Monitored infrastructure and resolved incidents to ensure data processing systems remained reliable and performant.• Optimized cloud-based data infrastructure across AWS and GCP to support scalable analytics workloads and reduce compute costs.• Provisioned cloud-native architectures tailored for data ingestion, storage, and analysis based on client needs.• Using Power BI to create, customize dashboards that meet the specific needs and analysis client• Utilized advanced SQL queries to join multiple relational database tables, creating comprehensive datasets for analysis.• Developed complex SQL queries for automation, which suppresses a lot of manual intervention• Maintain version control of objects for every code change using GitHub• Implemented Infrastructure as Code (IaC) with Terraform and configuration management using Ansible to streamline data ops workflows.• Containerized analytics tools and Python-based data processing scripts using Docker; deployed on AWS ECS for efficient scaling.• Utilized AWS EC2 instances for web servers within an Auto Scaling Group (ASG) for high availability and implemented an Application Load Balancer (ALB) to distribute traffic.• Configured a VPC for isolated networking with NAT for outbound internet access.• Implemented CI/CD with Git, AWS CodeBuild, CodeDeploy, and AWS CodePipeline for automated building and deployment of Docker containers.• Configured Jenkins to automatically trigger builds upon a Git pull request, integrating with SonarQube for code quality analysis.• Managed IAM roles and permissions for secure data access in S3, Redshift, Glue• Cleaned and joined disparate datasets using SQL joins, CTEs, and subqueries for unified reporting.