Cloud Data Engineering

Job Overview

We are seeking a highly skilled and experienced Cloud Data Engineer to join our Digital Technologies team. The ideal candidate will have 6-8 years of experience in designing, building, and maintaining cloud-based data solutions on Azure and AWS platforms. This role will require expertise in data integration, pipeline development, data modelling

Key Responsibilities

• Design, build, and optimize scalable, reliable, and efficient ETL/ELT pipelines for large data set processing.
• Automate data workflows to ensure real-time and batch data availability.
• Develop and manage data solutions using Azure services such as Data Factory, Synapse Analytics, Azure Databricks, and Azure SQL.
• Work with AWS services like Glue, Redshift, S3, Lambda, and Athena to create robust data solutions.
• Integrate structured, semi-structured, and unstructured data from various sources.
• Create and maintain data models that support analytics and reporting needs.
• Collaboration and Stakeholder Engagement:
• Work closely with cross-functional teams, including Data Scientists, Analysts, and Software Engineers.
• Translate business requirements into technical specifications for data solutions.
• Manage IAM roles, policies, and encryption for data at rest and in transit.

Qualifications

• Bachelors degree in computer science, Engineering, or a related field.
• 6-8 years of hands-on experience in cloud data engineering, with a focus on Azure and AWS.
• Proficiency in Python, SQL, and other scripting languages for data manipulation and automation.
• Experience in data orchestration tolls like Airflow and relevant cloud components.
• Strong understanding of distributed computing and big data frameworks like Apache Spark and Hadoop.
• Knowledge of Cloud data Warehouses like Synapse, Snowflake.
• Experience with CI/CD pipelines for data workflows using tools like Jenkins, GitHub Actions, or Azure DevOps.
• Certification in Azure/AWS and Databricks
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Strong problem-solving skills and the ability to work independently or as part of a team.

Performance Optimization

• Monitor and optimize the performance of cloud data pipelines and infrastructure.
• Debug and resolve data-related issues in a timely manner.