Cloud Data Engineer | Snowflake, Spark, dbt, SQL & AWS

Synechron; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

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. The role will collaborate with cross-functional teams to implement reliable cloud solutions, monitor performance and availability, provide technical support, and apply current industry practices.

The position contributes to business objectives by enabling scalable cloud services, efficient

Qualifications

• AWS proficiency in designing and maintaining cloud infrastructure and applications.
• Snowflake experience in cloud data warehouse environments.
• Spark experience with distributed data processing and data engineering workloads.
• dbt experience developing or supporting data transformation workflows.
• Strong SQL for data querying, transformation, validation, and development.
• Cloud platforms proficiency across AWS, Azure, and GCP.
• Familiarity with automation and configuration management tools like Terraform, Chef, Puppet.
• Knowledge of MySQL, PostgreSQL, and Oracle databases.
• Experience with virtualization technologies (VMware, Hyper-V).
• Ability to monitor and manage cloud environments for performance and availability.

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 meeting technical and business requirements.
• Support cloud infrastructure design, configuration, deployment, maintenance, and operational readiness.
• Monitor and manage cloud environments for performance, availability, reliability, and resource utilization.
• Develop and maintain data processing and transformation workflows using Spark, dbt, and SQL.
• Support database management across MySQL, PostgreSQL, Oracle, and cloud databases.
• Use Terraform, Chef, and Puppet to improve consistency and delivery efficiency.
• Support virtualization technologies as required by the environment.
• Provide technical support to clients on cloud-based solutions.

Skills

AWS

Snowflake

Apache Spark

dbt

SQL

Cloud platforms

Automation

Configuration management

Database management

Virtualization

Cloud monitoring

Tools

Terraform

Chef

Puppet

Job description

Job Summary

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. The role will collaborate with cross-functional teams to implement reliable cloud solutions, monitor performance and availability, provide technical support, and apply current industry practices. The position contributes to business objectives by enabling scalable cloud services, efficient data management, operational stability, and effective delivery of cloud-based solutions.

Required

Software Requirements (Required and Preferred)

• AWS: Proficiency in cloud computing platforms, with hands-on experience designing, implementing, and maintaining cloud infrastructure and applications.
• Snowflake: Experience supporting cloud data warehouse environments and data platform operations.
• Apache Spark: Experience with distributed data processing and data engineering workloads.
• dbt: Experience developing, managing, or supporting data transformation workflows.
• SQL: Strong experience with SQL for data querying, transformation, validation, and database development.
• Cloud platforms: Proficiency in cloud computing platforms, including AWS, Microsoft Azure, and Google Cloud Platform.
• Automation and configuration management: Familiarity with Terraform, Chef, and Puppet.
• Database management systems: Knowledge of MySQL, PostgreSQL, and Oracle.
• Virtualization technologies: Experience with VMware and Hyper-V.
• Cloud monitoring and management: Ability to monitor and manage cloud environments for performance and availability.
• Specific software versions are not defined in the requirements; candidates should have experience with versions applicable to the assigned technology environment.

Preferred

• Experience implementing data platforms using Snowflake, Spark, dbt, SQL, and AWS together.
• Experience with cloud infrastructure automation and configuration management.
• Experience optimizing cloud data workloads for performance, availability, maintainability, and responsible resource usage.
• Experience supporting multi-cloud environments involving AWS, Microsoft Azure, and Google Cloud Platform.
• Experience with data quality, data validation, data lineage, workflow orchestration, and monitoring.
• Experience with cloud-based technical support and incident resolution.

Overall 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.

Technical Skills (By Category)

Programming Languages

Essential

• 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.

Preferred

• Experience with programming or scripting languages used for Spark processing, cloud automation, and data engineering.
• Experience developing automation scripts for cloud infrastructure, data workflows, monitoring, or operational support.

Databases/Data Management

Essential

• Strong experience with SQL.
• Experience with Snowflake as a cloud data platform.
• Knowledge of database management systems, including MySQL, PostgreSQL, and Oracle.
• Understanding of data structures, data modeling, data transformation, data quality, and data validation.
• Experience developing or supporting data workflows using Spark and dbt.
• Ability to assess data platform performance, availability, reliability, and maintainability.

Preferred

• Experience with data warehousing, data integration, data lineage, metadata, reconciliation, and data governance.
• Experience optimizing SQL queries, Snowflake workloads, Spark jobs, and dbt models.
• Experience with data migration and integration across cloud and on-premises environments.

Cloud Technologies

Essential

• 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.
• Experience supporting cloud-based data engineering workloads.

Preferred

• Experience designing and supporting multi-cloud solutions.
• Experience with cloud-native data platforms and services.
• Experience implementing cloud cost optimization, resource efficiency, monitoring, and operational automation.
• Experience applying sustainable cloud practices to reduce unnecessary resource consumption.

Frameworks and Libraries

Essential

• 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.

Preferred

• Experience with reusable data engineering frameworks and transformation standards.
• Experience with workflow orchestration, data quality frameworks, monitoring libraries, and operational utilities.
• Experience supporting scalable data processing and transformation architectures.

Development Tools and Methodologies

Essential

• Familiarity with automation and configuration management tools, including Terraform, Chef, and Puppet.
• Experience with virtualization technologies, including VMware and Hyper-V.
• Experience with cloud monitoring, incident management, troubleshooting, and operational support.
• Ability to work independently and as part of a cross-functional team.
• Ability to apply structured delivery, documentation, change management, and support practices.

Preferred

• Experience with infrastructure as code and automated environment provisioning.
• Experience with continuous integration, continuous delivery, automated testing, deployment automation, and release management.
• Experience documenting cloud architectures, operational procedures, data workflows, and support processes.

Security Protocols

Essential

• 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 escalation cloud, infrastructure, data, and operational security risks.

Preferred

• Experience implementing security controls across AWS, Microsoft Azure, and Google Cloud Platform.
• Experience supporting access reviews, security assessments, audit activities, vulnerability remediation, and compliance requirements.
• Experience incorporating security and data protection checks into automated cloud deployment processes.

Experience Requirements

• 05-08 years of experience in cloud computing and virtualization.
• Relevant experience designing, implementing, maintaining, monitoring, and troubleshooting cloud infrastructure and applications.
• Experience with AWS, Microsoft Azure, and Google Cloud Platform.
• Experience with Snowflake, Spark, dbt, SQL, and cloud-based data engineering solutions.
• Experience with automation and configuration management tools such as Terraform, Chef, and Puppet.
• Experience with database management systems, including MySQL, PostgreSQL, and Oracle.
• Experience with virtualization technologies such as VMware and Hyper-V.
• Experience in a relevant industry, such as technology or finance.
• Experience providing technical support for cloud-based solutions is preferred.
• Candidates may qualify through an equivalent combination of cloud computing, virtualization, data engineering, database management, automation, and demonstrated delivery experience.

Day-to-Day Activities

• 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