| Title | Data Engineer |
| location | Remote |
| Type | Contract |
| Interview Mode: | Virtual |
Job Summary
Proficient in AWS, Databricks, and Azure DevOps, with a focus on strong analytical skills in PySpark, Delta Live Tables, Change Data Capture (CDC), and on-premises to AWS data migration.
Technical Skills
AWS (Amazon Web Services):
Core Services: Proficiency with core AWS services like EC2, S3, RDS, Lambda, and VPC.
Data Services: Experience with AWS data services Glue and EMR.
AWS DMS: Knowledge of AWS Database Migration Service (DMS) for migrating databases to AWS.
CDC: Understanding of Change Data Capture (CDC) techniques to capture and replicate changes from source databases to target databases.
Security: Understanding of AWS security best practices, IAM, and encryption.
Databricks:
PySpark & Spark SQL: Strong analytical skills in PySpark & Spark SQL for big data processing and analysis.
Delta Live Tables: Expertise in using Delta Live Tables for building reliable and scalable data pipelines.
Notebooks: Strong utilization of Databricks Notebooks for data analysis.
Workflows: Setting up and monitoring Databricks Workflows.
Data Integration: Experience integrating Databricks with AWS services.
DevOps Principles:
CI/CD Pipelines: CI/CD pipelines using Azure Pipelines.
Version Control: Proficiency with Azure Repos and Git for version control.
Automation: Scripting and automation using PowerShell, Bash, or Python. Automating the build, test, and deployment processes
Infrastructure as Code (IaC):
Terraform: Experience with Terraform for managing AWS and Azure infrastructure.
On Prem integration with AWS
Optimization and Monitoring:
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