Consulting Principal AWS Cloud Engineer

Senior Data Engineer

Data Engineer / Senior / Supervisor

Responsibilities: <ul><li>Demonstrated ability to drive cultural change and advocate for cloud transformation Key Responsibilities Cloud Strategy &amp; Leadership&nbsp;</li><li>Develop and implement a comprehensive AWS cloud strategy, ensuring alignment with business and technology goals.&nbsp;</li><li>Provide technical leadership and advocacy, championing cloud-native best practices and innovation.&nbsp;</li><li>Lead and drive architectural decisions, ensuring scalability, security, and operational efficiency.</li><li>Cloud Architecture &amp; Design&nbsp;</li><li>Architect secure, scalable, and highly available AWS cloud environments.&nbsp;</li><li>Develop and maintain enterprise-wide cloud blueprints, patterns, and frameworks to drive consistency.&nbsp;</li><li>Research and integrate emerging cloud technologies to foster continuous innovation. Infrastructure as Code &amp; Automation&nbsp;</li><li>Lead adoption and implementation of Infrastructure as Code (IaC) using Terraform, AWS CloudFormation, and Helm.&nbsp;</li><li>Design and optimize CI/CD pipelines to streamline cloud deployments and operations.&nbsp;</li><li>Implement self-healing and automated failover mechanisms to enhance resilience and reliability.</li><li>Kubernetes &amp; Cloud-Native Technologies&nbsp;</li><li>Manage and optimize Kubernetes clusters (EKS, Helm, IAM) for scalability and security.&nbsp;</li><li>Define and enforce best practices for containerized applications and orchestration.&nbsp;</li><li>Improve Kubernetes networking, ingress, and observability solutions to enhance performance. Security &amp; Compliance&nbsp;</li><li>Establish and enforce security best practices for AWS environments, including IAM, WAF, Secret Manager, and encryption.&nbsp;</li><li>Implement zero-trust security models and secure multi-account AWS environments.&nbsp;</li><li>Conduct security audits, incident response, and ensure compliance with industry standards. Monitoring, Logging &amp; Reliability Engineering.</li><li>Deploy and manage monitoring tools (DataDog, Splunk, CloudWatch, Coralogix) to ensure visibility and observability.&nbsp;</li><li>Implement SRE principles to enhance system uptime, reliability, and efficiency.&nbsp;</li><li>Conduct post-mortem analysis and drive continuous improvements in cloud performance. Collaboration &amp; Thought Leadership&nbsp;</li><li>Work closely with software developers, system engineers, and security teams to design and implement cloud solutions.&nbsp;</li><li>Provide mentorship, training, and technical leadership to engineering teams.&nbsp;</li></ul> Requirements: <ul><li>10+ years of experience in IT, with at least 5+ years in AWS cloud engineering and architecture.</li><li>Deep understanding of AWS services, including EC2, EKS, RDS, S3, Lambda, VPC, IAM, Transit Gateway, and CloudFormation.&nbsp;</li><li>Expertise in Kubernetes (EKS, Helm, Daemon Sets, StatefulSets, Karpenter, external-dns, aws-cni).&nbsp;</li><li>Strong experience with Terraform, CloudFormation, and automation scripting (Bash, Python, PowerShell).&nbsp;</li><li>Hands-on experience managing CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps).&nbsp;</li><li>Proficiency in monitoring and logging tools (DataDog, Splunk, Coralogix, CloudWatch).&nbsp;</li><li>Strong networking and security knowledge (DNS, VPC, NAT, Security Groups, IAM).&nbsp;</li><li>Experience designing and developing scalable, production-grade software tools and automation scripts using Python. Preferred Certifications&nbsp;</li><li>AWS Certified Solutions Architect – Professional (or equivalent).&nbsp;</li><li>Additional certifications in Kubernetes (CKA), AWS Security, or DevOps are a plus. Leadership &amp; Soft Skills&nbsp;</li><li>Proven experience leading cloud architecture and strategy initiatives.&nbsp;</li><li>Ability to mentor and guide technical teams in a fast-paced, agile environment.&nbsp;</li><li>Strong problem-solving and troubleshooting skills in complex cloud environments.</li><li>Excellent communication skills with the ability to translate technical concepts for engineering, business, and executive stakeholders.&nbsp;</li></ul>

Responsibilities: <ul><li>Develop and maintain data pipelines for efficient extraction, transformation, and loading (ETL) processes.</li><li>Design and optimize data storage solutions, including Amazon Redshift data warehouses and Amazon S3 data lakes</li><li>Ensure data quality and integrity through validation, cleansing, and error handling processes.</li><li>Collaborate with data analysts, data architects, and software engineers to understand data requirements and deliver relevant data sets for business intelligence.</li><li>Implement data security measures and access controls to protect sensitive information.</li><li>Automate and improve data processes and workflows for scalability and efficiency.</li><li>Monitor data infrastructure performance and address any issues promptly.</li><li>Stay updated on industry trends and emerging technologies in data engineering.</li><li>Document data pipelines, processes, and best practices to facilitate knowledge sharing.</li><li>Continuously optimize data architecture to support the companys evolving data needs.</li><li>Work cross-functionally to drive data-driven decision-making within the organization.</li></ul> Requirements: <ul><li>Bachelors degree in Computer Science, Information Technology.</li><li>Minimum 6 years of experience in data engineering - CS</li><li>Knowledge of AWS services, particularly Glue, Redshift and S3.</li><li>Data Storage and Management - Amazon S3, Amazon RDS and DynamoDB</li><li>Data Processing and ETL - AWS Glue</li><li>Data Warehousing - Amazon Redshift</li><li>Programming and Scripting:</li><li>Proficiency in languages like Python, Java, or Scala for data manipulation and automation.</li><li>Data Modeling and Architecture&nbsp;</li><li>Monitoring and Optimization - Using AWS CloudWatch for monitoring and optimizing data workflows</li><li>Proficiency in SQL and database management.</li><li>Experience with ETL (Extract, Transform, Load) processes.</li><li>Familiarity with data warehousing and cloud platforms (AWS, Azure, or Google Cloud).</li><li>Strong data modeling skills</li></ul>

Role Description:The Data Engineering Senior Supervisor will lead a small team of data engineering professionals to design, build and operate high performance data centric products or solutions through the use of modern engineering practices and technologies.In this role, you will provide guidance to ensure the delivered data centric products or solutions are scalable, sustainable and robust.You will also lead team development and cross team relationships and delivery to advance the company's engineering delivery.Responsibilities:Lead a local or regional team of engineering professionals that design, develop, deploy and enhance new and existing data centric products or solutions through the use of modern platforms and technologies.Provide routine inputs and guidance to the data engineering team on business requirements analysis, technical specification's preparation, product delivery, testing and operation to support businesses strategic direction.Coach engineers, share relevant technical approaches, identify new trends, modern skills and present new methodologies within the data engineering community.Lead and develop a team, coach and make decisions related to talent management, hiring, performance, and disciplinary actions.Other duties as assignedRequirements:Minimum QualificationsBachelor's degree in a related field or equivalent experience.Minimum of four years of related work experience.Minimum of two years leading a team of Data Engineers.Preferred QualificationsConfirmed data engineering experience with data storage and management of large, heterogenous datasets, including formats, structures, and cataloging with such tools as Iceberg, Parquet, Avro, ORC, S3, HFDS, HIVE, Kudu or others.Experience leading Big Data engineering teams working in environments such as Hadoop and SparkExperience leading technology strategies with cloud Platforms including AWS, GCP or AzureExperience leading engineering teams working in streaming and stream integration or middleware platforms, tools, and architectures such as Kafka, Flink, JMS, or Kinesis.Confirmed knowledge of best practice patterns and how to apply them to modern data architectures, including data warehouses, data lakes, data mesh, hubs and associated capabilities including ingestion, governance, modeling, observability and more.Experience leveraging transformation and modeling tools, including SQL based transformation frameworks, orchestration and quality frameworks including dbt, Apache Nifi, Talend, AWS Glue, Airflow, Dagster, Great Expectations, Oozie and others.Strong programming knowledge of SQL, Python, R, Java, Scala or equivalent.Proficiency in engineering tooling including docker, git, and container orchestration services.Strong experience leading devops teams with demonstratable understanding of associated best practices for code management, continuous integration, and deployment strategies.Experience and knowledge of data governance considerations including quality, privacy, security associated implications for data product development and consumption.A passion for quality and continuous improvement with an owners mindset.Ability to work effectively as part of a team, group and cultureAbility to navigate ambiguity and work in agile ways.

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Consulting Principal AWS Cloud Engineer

Senior Data Engineer

Data Engineer / Senior / Supervisor

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Consulting Principal AWS Cloud Engineer

Senior Data Engineer

Data Engineer / Senior / Supervisor

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow
WhiteCrow is on a mission to connect companies with the best talent across the globe.