Description

Design, build, and maintain cloud-based data infrastructure and pipelines to support analytics and business intelligence.

Responsibilities

• Design and implement scalable data architectures across AWS, Azure, or GCP environments.
• Build and manage cloud-based data warehouses including Snowflake, Redshift, or BigQuery.
• Develop and optimize ETL/ELT pipelines for data ingestion, transformation, and processing.
• Automate workflows using Apache Airflow, AWS Glue, or Azure Data Factory.
• Ensure data security and compliance through encryption and role-based access control.

Required Skills

• 5+ years of experience in data engineering.
• Strong programming skills in Python, Java, or Scala.
• Proficiency in SQL and NoSQL databases such as PostgreSQL, MongoDB, or DynamoDB.
• Experience with AWS services including S3, Redshift, Glue, Lambda, EMR, and Kinesis.
• Experience with Azure services including Data Factory, Synapse, Cosmos DB, and Blob Storage.
• Experience with GCP services including BigQuery, Dataflow, Pub/Sub, and Cloud Storage.
• Knowledge of Infrastructure as Code using Terraform or CloudFormation.
• Experience with CI/CD pipelines for data deployment.

Preferred Skills

• Certifications such as AWS Certified Data Analytics or Google Professional Data Engineer.
• Experience with Kubernetes and Docker for containerized data applications.

Bachelor’s or Master’s degree in Computer Science, Data Engineering, IT, or a related field.

Key Skills

Education

Any Gradute