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

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.

Software Requirements (Required and Preferred) Required 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 escalate 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, 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 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.

Professional Competencies 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.

Adapt to a fast-paced, high-pressure, and rapidly changing work environment while maintaining service quality and delivery focus.

Identify opportunities to improve cloud services through automation, workload optimization, technology evaluation, and sustainable resource usage.

Prioritize and manage multiple tasks, incidents, project activities, and support responsibilities according to business and service needs.

Soft Skills Strong communication and interpersonal skills.

Ability to work effectively in a fast-paced, high-pressure environment.

Ability to prioritize and manage multiple tasks simultaneously.

Strong customer-focused approach.

Positive and professional approach to technical support and stakeholder interactions.

Ability to work independently and as part of a team.

Ability to adapt to a rapidly changing work environment.

Strong problem-solving and troubleshooting skills.

Ability to collaborate effectively with cross-functional teams and clients.

S​ YNECHRON’S DIVERSITY & INCLUSION STATEMENT   Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law .

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