Engineer, Data & Cloud, Clark Capital

Raymond James•Philadelphia, PA

8d•Hybrid

About The Position

Clark Capital is seeking a Data & Cloud Engineer to build and support the data pipelines and cloud infrastructure that power our reporting, analytics, applications, and AI capabilities. The ideal candidate will bring five or more years of experience in data engineering, cloud engineering, platform engineering, or a related discipline, with hands-on experience developing production ETL/ELT pipelines, working with Snowflake, and administering AWS resources. This role will work closely with our Data Engineering team and collaborate across Development, AI, Information Security, and Infrastructure. In addition to developing pipeline logic and data models, the engineer will own platform administration, access provisioning, and governance across Snowflake and AWS. The successful candidate will be a collaborative, hands-on engineer who can solve complex technical problems and take ownership from design through production support.

Requirements

Minimum of five years of experience in data engineering, cloud engineering, platform engineering, or a related technical role supporting production systems.
Ability to communicate technical concepts, risks, incidents, and recommendations clearly to technical and business stakeholders.
Strong analytical, troubleshooting, and root-cause analysis skills.
Demonstrated attention to detail.
Ability to prioritize project work, operational responsibilities, and production issues in a high-accountability environment.
Experience developing and deploying software using the Agile methodologies
Security-first mindset with a practical understanding of least privilege, data protection, secrets management, encryption, and auditable access controls.
Solutions-oriented and accountable, with the ability to take ownership of ambiguous technical problems and drive them from investigation through sustainable resolution.
Commitment to continuous improvement through automation, documentation, standardization, and the elimination of recurring operational issues.

Nice To Haves

Hands-on experience developing production ETL/ELT pipelines, working with Snowflake, and administering AWS resources.
Experience with Matillion or similar technologies.
Experience with Terraform or AWS CloudFormation.
Experience with Snowflake administration (roles, warehouses, resource monitors, query performance, usage and cost controls).
Experience with AWS resource administration (S3, CloudWatch, EventBridge, Secrets Manager, KMS).
Experience with Bitbucket.

Responsibilities

Design, build, test, deploy, and maintain scalable ETL/ELT pipelines using Matillion or similar technologies to support reporting, analytics, applications, and AI.
Develop and optimize complex SQL transformations and data models in Snowflake, emphasizing performance, maintainability, testing, and data quality.
Develop and deploy Python-based automation and serverless workflows, including AWS Lambda functions, to support data ingestion, orchestration, and recurring operational tasks.
Use infrastructure-as-code practices and tools, such as Terraform or AWS CloudFormation, to provision and maintain cloud resources consistently.
Administer and optimize the Snowflake environment, including roles, warehouses, resource monitors, query performance, usage and cost controls.
Administer and support AWS resources used by the data platform, including S3, CloudWatch, EventBridge, Secrets Manager, and KMS.
Implement monitoring and alerting across pipelines and platform services to surface health, performance, and data quality issues before they reach the business.
Manage least-privilege, role-based access across Snowflake, AWS, Bitbucket, and related platforms, partnering with Information Security and Infrastructure to implement and review IAM roles, policies, and service accounts.
Implement secure data sharing and integration with custodians, external partners, and vendors.
Create and maintain architecture diagrams, data-flow documentation, operational runbooks, and platform standards.
Participate in production support and incident resolution, troubleshooting data quality, performance, and reliability issues and converting recurring failures into permanent fixes, monitoring rules, or runbook entries.