Cloud Solutions Architect
2 weeks ago
Americold Logistics is a leading global provider of temperature-controlled supply chain solutions. We collaborate with agricultural producers and food manufacturers to ensure that their perishable and frozen goods reach food distributors, restaurants, and grocery stores without spoilage.
Our clientele, which includes some of the most esteemed brands in the food sector, relies on our expertise and unwavering commitment to safety to fulfill their obligations.
What You'll Do
You will take charge of designing, constructing, deploying, and maintaining business applications for Americold's cloud infrastructure and technologies.
As a seasoned technologist and vital team member, you will influence architectural decisions across diverse use cases involving security, data lakes, analytics, and AI/ML.
The ideal candidate will demonstrate a strategic mindset regarding business, product, and technical challenges. You will provide exceptional technical design guidance and thought leadership.You will collaborate closely with business and cross-functional technical teams to optimize existing cloud solutions and propose new cloud-based strategies for migrating current workloads, assisting with cloud transition efforts, reviewing workload architectures, and offering guidance on addressing high-risk issues.
You will lead initiatives to capture and disseminate best-practice knowledge among technical data engineers and analysts.Responsibilities include architecting, designing, and maintaining scalable, cost-effective, and efficient cloud solutions on data lakes while ensuring compliance with best practices.
Design, build, and implement proof-of-concept solutions, cloud architectures, and applications.
Work closely with stakeholders and product teams to comprehend business objectives, bridging the gap between technical and non-technical stakeholders to create cloud-based solutions that facilitate those objectives.
Communicate effectively with stakeholders and develop applications to meet project requirements. Collaborate with teams in Business Operations, Sales/Business Development, Finance, and Customers to maintain secure cloud environments and prevent downtime or security breaches.
Look for opportunities to transition legacy systems and solutions to the cloud for enhanced efficiency.Identify upgrades and enhancements to current cloud architectures. Implement solutions utilizing AWS cloud offerings such as EC2, S3, Lambda, Glue jobs, etc.
Ensure that the architecture and solutions adhere to cloud best practices and mitigate potential security vulnerabilities.
Provide technical support for cloud-related issues, monitor solutions, and implement strategies to eliminate performance bottlenecks. Utilize tools such as IAM, resource tagging, and cost management to enforce cloud governance policies and implement monitoring and alerting solutions proactively.Scale our cloud data infrastructure, data pipelines, and tools to meet expanding business needs. Evaluate and enhance data quality and reliability. Manage and collaborate with data engineers and analysts throughout all phases of the SDLC. Stay updated on the latest trends and advancements in data science, machine learning, and cloud technologies, applying this knowledge to drive innovation within the organization.
Lead the design, development, and deployment of ML pipelines and data solutions in cloud environments such as AWS, Microsoft Azure, and Google Cloud Platform (GCP), with a focus on AWS.
Develop and implement advanced machine learning models and algorithms to address complex business challenges.
What Experience and Education You Need
Bachelor of Science degree in Computer Science or equivalent; or an equivalent combination of education and experience. Proven experience architecting complex systems and working on large-scale projects in AWS Cloud and Data Lake.
10 years of experience in designing, implementing, and maintaining data engineering solutions, with 5 years in cloud architecture/solutions, preferably AWS. Strong knowledge of cloud concepts, architectural patterns, and best practices. AWS Solution Architect, Associate or Professional certification is a plus. Proficient SQL skills, capable of performing effective queries involving multiple tables and subqueries. Experience with data mining principles: predictive analytics, machine learning, mapping, and collecting data from various data systems, both on-premises and cloud-based.
Experience designing Data Warehouse/Data Lake, Cloud-Based Technologies (AWS - Data Migration Service, Glue, S3, EC2, Lambda, Step Functions, Document DB, RedShift/Spectrum).
What Could Set You Apart
Familiarity with big data technologies such as Hadoop, Spark, and Kafka. Understanding of Generative AI. Knowledge of containerization and orchestration tools such as Docker and Kubernetes.
Experience with CI/CD pipelines and infrastructure as code (IaC) tools like Terraform or CloudFormation. Knowledge of leveraging and enhancing the Agile Scrum Process and DevSecOps practices. Proficiency in programming languages commonly used in Data Science applications (e.g., R, Python, Pyspark, Scala,...
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