Overview

Synechron is seeking a Cloud Data Engineer specializing in Snowflake, Spark, dbt, SQL, and AWS to design, implement, maintain, and support cloud infrastructure, data platforms, and cloud-based applications.

Responsibilities

• Design, implement, and maintain cloud infrastructure, data platforms, and applications using Snowflake, Spark, dbt, SQL, and AWS.
• Collaborate with cross-functional teams to implement cloud-based solutions that meet defined technical and business requirements.
• Support cloud infrastructure and data platform design, configuration, deployment, maintenance, and operational readiness.
• Monitor and manage cloud environments to ensure optimal performance, availability, reliability, and resource utilization.
• Develop and maintain data processing and transformation workflows using Spark, dbt, and SQL.
• Support database management activities across MySQL, PostgreSQL, Oracle, and applicable cloud database environments.
• Use automation and configuration management tools such as Terraform, Chef, and Puppet to improve consistency and delivery efficiency.
• Support virtualization technologies, including VMware and Hyper-V, where required by the environment.
• Provide technical support to clients in the use and operation of cloud-based solutions.
• Troubleshoot cloud infrastructure, data processing, database, virtualization, and application issues.
• Apply strong problem-solving and troubleshooting skills to identify root causes and implement effective corrective actions.
• Stay current with industry trends and best practices to enhance cloud services and data engineering capabilities.
• Promote sustainable technology practices through efficient cloud resource usage, workload optimization, automation, and maintainable solution design.
• Deliver reliable, secure, and supportable cloud solutions in line with agreed performance, availability, and service expectations.
• Strong SQL skills for querying, transformation, validation, data analysis, and database development.
• Ability to work with data processing logic and transformation workflows relevant to Spark, dbt, Snowflake, and AWS.
• Ability to create maintainable and reusable data engineering solutions.
• Design, implement, maintain, and troubleshoot cloud infrastructure, Snowflake data platforms, Spark processing, dbt transformations, SQL workflows, and AWS-based applications.
• Collaborate with cross-functional teams through solution planning, technical discussions, implementation activities, service reviews, and operational support meetings.
• Monitor cloud environments and data workloads, investigate performance or availability issues, and deliver configuration, automation, documentation, and support outputs.
• Provide technical guidance and support to clients, prioritize incidents and tasks, and make assigned operational and implementation decisions within defined standards and responsibilities.

Qualifications

• Strong experience with SQL.
• Knowledge of database management systems, including MySQL, PostgreSQL, and Oracle.
• Understanding of data structures, data modeling, data transformation, data quality, and data validation.
• Ability to assess data platform performance, availability, reliability, and maintainability.
• Proficiency in AWS.
• Proficiency in Microsoft Azure and Google Cloud Platform.
• Ability to design, implement, maintain, monitor, and troubleshoot cloud infrastructure and applications.
• Understanding of cloud performance, availability, scalability, networking, storage, security, and resource management.
• Apache Spark for distributed data processing.
• dbt for data transformation and model management.
• Snowflake for cloud data warehousing and data platform solutions.
• Ability to integrate data processing, transformation, storage, and cloud infrastructure components.
• Familiarity with automation and configuration management tools, including Terraform, Chef, and Puppet.
• Ability to work independently and as part of a cross-functional team.
• Ability to apply structured delivery, documentation, change management, and support practices.
• Awareness of cloud security principles and secure infrastructure management.
• Understanding of identity and access management, authentication, authorization, encryption, network security, and data protection.
• Ability to protect sensitive data in Snowflake, databases, cloud platforms, and data processing workflows.
• Ability to identify, document, and escalate cloud, infrastructure, data, and operational security risks.
• 05–08 years of experience in cloud computing and virtualization.
• Relevant experience designing, implementing, maintaining, monitoring, and troubleshooting cloud infrastructure and applications.
• Candidates may qualify through an equivalent combination of cloud computing, virtualization, data engineering, database management, automation, and demonstrated delivery experience.
• Bachelor's degree in Computer Science, Information Technology, or a related field; an equivalent combination of education and relevant professional experience may be considered.
• 05–08 years of experience in cloud computing and virtualization, with relevant experience in cloud data engineering and platform support.
• Certifications in cloud computing platforms, such as AWS Certified Solutions Architect or Microsoft Certified: Azure Administrator Associate, are preferred.
• Complete relevant training in AWS, Microsoft Azure, Google Cloud Platform, Snowflake, Spark, dbt, SQL, infrastructure automation, virtualization, and cloud security as applicable.
• Maintain continuous professional development by staying current with cloud computing, data engineering, automation, virtualization, security, and industry best practices.
• Apply structured critical thinking, problem-solving, and troubleshooting skills to resolve cloud, data, infrastructure, database, and application issues.
• Collaborate effectively with cross-functional teams while working independently on assigned cloud engineering and operational responsibilities.
• Communicate clearly with technical teams, clients, and stakeholders regarding requirements, incidents, technical solutions, progress, and risks.