Responsibilities :

• Design, develop, and implement robust and scalable data architectures and pipelines on AWS, with the capability to utilize Azure services when necessary.

• Optimize data ingestion and transformation processes using AWS services such as AWS Glue, Lambda, and EMR, and incorporate Azure services like Azure Data Factory if required .

• Strong expertise in AWS data services such as S3, Glue, Redshift, RDS, DynamoDB, and Lambda.

• Familiarity with Azure data services such as Azure Data Factory, Azure Data Lake, or Azure Synapse Analytics.

• Experience with data transformation and ETL tools.

• Proficiency in programming languages like Python, SQL, or similar for data manipulation and analysis.

• Develop and manage data models and databases using AWS solutions like RDS, Redshift, and DynamoDB, and integrate with Azure SQL Database or Cosmos DB as needed.

• Work closely with analytics and business teams to understand data requirements, ensuring solutions align with business goals.

• Maintain data quality and integrity through effective monitoring and validation processes.

• Implement security best practices for data handling and storage within both AWS and Azure environments.

• Automate data workflows and infrastructure using tools like Terraform, AWS CloudFormation, or Azure Resource Manager.

• Troubleshoot and resolve complex issues related to data processing and storage across cloud platforms.

Qualifications :

• Bachelor’s degree in Computer Science , Data Science, Information Technology, or a related field, or equivalent experience.

• 3-8 years of experience in data engineering, with significant exposure to AWS services and some experience with Azure.

• Proficiency in AWS data services such as S3, Glue, Redshift, RDS, DynamoDB, and Lambda.

• Familiarity with Azure data services such as Azure Data Factory, Azure Data Lake, or Azure Synapse Analytics.

• Experience with data transformation and ETL tools.

• Strong programming skills in languages like Python, SQL, or similar for data manipulation and analysis.

• Knowledge of big data technologies such as Hadoop, Spark, or Kafka.

• Excellent problem-solving skills with a detail-oriented approach.

• Strong communication skills and the ability to collaborate effectively with cross-functional teams.

Preferred Qualifications :

• AWS Certified Data Analytics or Azure Data Engineer Associate certification.

• Experience with data visualization tools such as Tableau, Power BI, or AWS QuickSight .

• Knowledge of machine learning frameworks and tools.

• Experience working in Agile environments and familiarity with Agile methodologies.

Azure GCP

years of experience required: