Data Engineer

Summary

I'm a Data Engineer with 5 years of experience. In my first year, I worked with AWS Cloud Platform for a retail company, focusing on managing and improving their data systems. Then, for the next 4 years, I shifted to Azure with a fintech company. Here, my role was more in-depth, dealing with large data sets and ensuring everything worked smoothly and securely, critical for finance operations.

Throughout, I've learned a lot about both AWS and Azure, and I'm excited about new challenges and learning opportunities in data engineering.

Expectations

In my next role, I'm looking for an opportunity that allows me to leverage my years of experience in data engineering, particularly within AWS and Azure platforms, while also challenging me to grow. I am eager to work on projects that drive innovation, particularly those that push the boundaries of what we can achieve with data and cloud technologies.

Additionally, I want to be part of a team that values collaboration and learning, where I can exchange insights with peers and continue enhancing my skills. I am also looking for a position that allows for a greater degree of responsibility and leadership, as I am ready to take on more advanced challenges and help guide strategic decisions based on my experiences in the retail and fintech sectors.

Lastly, a company culture that prioritizes employee growth and ethical data practices is important to me, as I believe that such an environment creates a strong foundation for success and innovation.

Employment Preferences

Expected Base Salary

**,000 USD

Expected Hourly Rate

** USD/hr

Academic Degree

Experience

Skills

• Programming Languages
• Python
• Java
• Cobol
• TypeScript
• Shell Scripting.
• Frameworks
• Spark
• Hadoop
• Kafka
• CI
• CM Tools
• Linux
• Red Hat
• CENTOS
• Ubuntu
• Windows.
• Cloud Systems
• Docker
• Azure
• AWS.
• Microsoft Azure
• Active Directory
• Applications Insights
• Azure Monitoring
• Key Vault
• Blob Storage
• Azure Search
• Data Factory
• Databricks
• SQL Azure
• Azure Analysis Services.
• Amazon Web Services
• EC2
• IAM
• S3
• Glue
• Glacier
• ELB
• DynamoDB
• ECS
• ECR
• EKS
• Code Deploy
• Code Build
• Code Pipeline
• CloudWatch
• SNS
• CloudFormation
• SageMaker
• Step Function
• Redshift
• Glue.
• Operating System
• Windows
• DOS
• Unix
• Linux. IAAC Tools
• AWS Cloud Formation
• Terraform. Version Control Tools
• GIT
• GitHub
• Bitbucket.
• Bug Tracking Tools
• Jira
• Asana
• IBM Clear Quest
• DevOps
• CD
• Agile
• Airflow
• Automation
• DevOps.
• Monitoring Tools
• AWS Cloud Watch
• Splunk.
• Application Servers
• Tomcat
• JBOSS
• Apache
• WebSphere
• WebLogic Databases
• MySQL
• DB2
• Cassandra
• MongoDB
• Snowflake. Development Methods
• Scrum
• Waterfall.
• IDEs
• PyCharm
• IntelliJ
• VsCode
• Jupyter Notebook.
• Data Visualization
• Tableau
• Power BI
• Kibana