Lead AWS Cloud Engineer - Databricks Platform

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We Are Looking For

Lead AWS Cloud Engineer - Databricks Platform

Location: Princeton, NJ (Hybrid - 3 days onsite)

Duration: Contract Or FTE

Position Overview

We are seeking a highly skilled and experienced AWS Cloud Engineer with a strong background in Databricks to join our dynamic cloud engineering team. The ideal candidate will have extensive experience in designing, deploying, and managing cloud infrastructure on AWS, along with in-depth expertise in the Databricks platform for data engineering, analytics, and machine learning workloads. The candidate should also have prior leadership experience, as they will be responsible for guiding a team of engineers in cloud-related initiatives, best practices, and ensuring the successful delivery of data-driven solutions.

Key Responsibilities

• Cloud Infrastructure Design & Implementation:
• Lead the design, implementation, and optimization of scalable and secure AWS cloud solutions.
• Utilize AWS services such as EC2, S3, Lambda, RDS, VPC, IAM, and others for building robust cloud-based architectures.
• Work closely with the architecture team to define infrastructure requirements and recommend suitable AWS technologies.
• Databricks Platform Expertise:
• Leverage Databricks for building and managing data pipelines, running Spark-based analytics workloads, and orchestrating machine learning models.
• Design, optimize, and maintain Databricks clusters and notebooks for data processing, transformation, and analysis.
• Integrate Databricks with other AWS services (e.g., S3, Redshift, Glue) to build comprehensive end-to-end data solutions.
• Provide leadership in best practices for working with Databricks to ensure reliability, scalability, and efficiency of data workflows.
• Leadership & Mentoring:
• Lead a team of cloud engineers, guiding them in implementing solutions that align with organizational goals and industry best practices.
• Mentor junior team members and provide technical guidance on cloud-related projects, Databricks integration, and infrastructure optimization.
• Facilitate cross-functional collaboration between engineering, data science, and business teams.
• Automation & Optimization:
• Automate cloud infrastructure provisioning and management using Infrastructure-as-Code tools (e.g., Terraform, CloudFormation).
• Continuously monitor and optimize AWS resources to improve performance and reduce costs.
• Troubleshooting & Support:
• Provide expert-level troubleshooting and support for cloud infrastructure, Databricks platform issues, and production systems.
• Identify and resolve performance bottlenecks, security risks, and system inefficiencies across AWS and Databricks environments.
• Documentation & Reporting:
• Document cloud infrastructure, Databricks configurations, and solutions for internal knowledge sharing.
• Prepare regular reports on system performance, cost management, and the status of cloud initiatives.
  
  

Key Requirements

• Experience:
• 5 years of experience in AWS cloud engineering, with a proven track record of delivering cloud-based solutions.
• 3 years of hands-on experience with Databricks platform, including building and managing data pipelines, notebooks, and Spark-based workloads.
• 2 years of experience leading or mentoring a team of engineers, with strong leadership and team-building skills.
• Technical Skills:
• Proficient in AWS cloud services (EC2, S3, Lambda, RDS, VPC, IAM, CloudWatch, etc.).
• Strong knowledge of Databricks, Apache Spark, and data engineering best practices.
• Experience with containerization and orchestration tools (Docker, Kubernetes).
• Familiar with Infrastructure-as-Code tools (Terraform, CloudFormation).
• Experience with data processing frameworks, data lakes, and analytics pipelines.
• Additional Skills:
• Strong understanding of security best practices in cloud environments.
• Ability to manage complex cloud projects with multiple stakeholders.
• Excellent communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Experience with Agile methodologies is a plus.
  
  

Education & Certifications

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent experience).
• AWS Certified Solutions Architect – Professional (preferred).
• Databricks Certified Associate Developer (preferred, but not required).
  
  

At Greymatter Innovationz,

We Offer

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