Senior Cloud Data Engineer - Snowflake, DBT, Airflow and AWS

About the role

Synechron is seeking a Senior Cloud Data Engineer with strong expertise in Snowflake, DBT, Apache Airflow and AWS to design, develop and support scalable cloud data platforms. The role combines hands-on data engineering, cloud platform implementation, infrastructure automation, solution design, architecture discussions and stakeholder engagement, delivering reliable, secure and maintainable data solutions.

Key responsibilities

• Design, develop and support scalable cloud-based data platforms on AWS.
• Build, optimize and maintain ELT/ETL pipelines using Snowflake, DBT and Apache Airflow.
• Develop reliable, reusable, tested and documented data models and transformation workflows.
• Participate in solution design, architecture discussions, technical decision-making and design reviews.
• Implement and manage infrastructure as code with Terraform and/or CloudFormation.
• Develop and maintain CI/CD pipelines for data platform deployments.
• Collaborate with business stakeholders, architects, data, engineering, security and operations teams.
• Troubleshoot production issues, pipeline failures, data-quality concerns and performance bottlenecks, and take part in incident response and root-cause analysis.
• Drive best practices around automation, data governance, monitoring, observability and cloud optimization.
• Contribute to technical leadership, review designs and guide implementation decisions.

Required profile

• Minimum 4-6 years of hands-on experience with Snowflake, DBT, Apache Airflow and AWS.
• Experience with data warehousing, data modeling, data integration and data transformation.
• Experience with source control (GitHub/Git) and CI/CD tools such as Buildkite, Azure DevOps, Jenkins or GitHub Actions.
• Preferred: enterprise-scale cloud platform implementation, cloud-native architectures, data lake or lakehouse patterns, data governance and metadata management, and Agile delivery tools.

Required skills

• Python for data engineering, automation, orchestration and testing.
• Advanced SQL for data transformation, validation and optimization.
• Snowflake, DBT and Apache Airflow.
• AWS cloud services, including IAM and security controls.
• Terraform and/or CloudFormation for infrastructure as code.
• Preferred: AWS data, storage, compute, networking and serverless services; data cataloguing and governance tools.