AWS Lead

Job Overview

We are seeking an experienced AWS Lead to provide technical leadership in the architecture, design, delivery, and continuous improvement of modern data platforms built on Amazon Web Services (AWS).

The role will lead the development of scalable, secure, governed, and cost-efficient cloud data solutions supporting enterprise analytics, business intelligence, data engineering, and, where applicable, AI and machine learning workloads.

The successful candidate will bring extensive experience in data and analytics platforms, combined with strong AWS architecture expertise and the ability to translate business requirements into practical cloud data strategies. The role will work closely with business stakeholders, data engineering and analytics teams, cloud and security specialists, and other technology stakeholders to establish architecture standards, guide delivery, and ensure enterprise-ready solutions.

This is a senior technical leadership position combining cloud architecture, data platform strategy, solution design, delivery oversight, technical governance, stakeholder engagement, and technical mentoring.

Key Responsibilities

AWS Data Platform Architecture & Leadership

• Lead the architecture and design of enterprise-scale modern data platforms using AWS.
• Define scalable architectures covering data lakes, data warehouses, and lakehouse environments based on business and technical requirements.
• Establish reusable architecture patterns and technical standards for data ingestion, integration, modelling, governance, security, and access.
• Provide technical direction to data engineers, developers, consultants, and other delivery teams.
• Review solution designs and implementations to ensure alignment with architecture, security, scalability, performance, and cost requirements.
• Provide technical guidance on AWS service selection and appropriate architecture patterns for different data workloads.

Data Platform Design & Delivery

• Lead the design and implementation of modern data platforms using AWS services such as:
• Amazon S3
• AWS Glue
• Amazon Redshift
• Amazon Athena
• Amazon Kinesis
• Oversee the development of data ingestion, transformation, integration, and analytics pipelines.
• Support appropriate processing patterns across batch, streaming, and near real-time data workloads.
• Enable reliable data consumption for analytics, business intelligence, reporting, and downstream applications.
• Ensure data platform solutions are designed for scalability, reliability, maintainability, and operational readiness.

Data Engineering & Analytics

• Provide technical leadership for the development and optimization of ETL/ELT pipelines.
• Guide the design of data models, schemas, and analytics-ready datasets.
• Apply strong SQL and data modelling practices across enterprise data solutions.
• Establish approaches for data quality, metadata, and lineage.
• Support the architecture and integration of AI/ML and advanced analytics workloads where applicable.
• Ensure data solutions can support evolving business and analytical requirements.

Cloud Security, Governance & Optimization

• Ensure AWS data platforms follow appropriate security and governance practices.
• Apply principles covering IAM, access control, data security, networking, and governance.
• Establish appropriate controls for protecting enterprise data throughout the data lifecycle.
• Drive platform cost optimization and ensure AWS resources are designed and operated efficiently.
• Promote secure-by-design and governance-by-design approaches across data platform implementations.

Platform Operations & Lifecycle Management

• Provide technical oversight for platform monitoring, performance management, and operational stability.
• Establish appropriate practices for platform environment management and lifecycle management.
• Support CI/CD and automated deployment practices for data platform components.
• Identify opportunities to improve reliability, scalability, performance, and cost efficiency.
• Establish and maintain technical documentation, architecture standards, operational runbooks, and best practices.

Stakeholder & Delivery Leadership

• Partner with business stakeholders to understand strategic objectives, data requirements, and analytics use cases.
• Translate business requirements into practical AWS data architecture and implementation approaches.
• Advise stakeholders on AWS data services, architecture options, and technical trade-offs.
• Collaborate with data engineers, analysts, data scientists, cloud architects, security teams, and project stakeholders.
• Provide technical leadership throughout the solution lifecycle, from architecture and design through implementation and operational readiness.
• Mentor and provide technical guidance to junior engineers, consultants, and delivery team members.

Required Qualifications & Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Analytics, or a related discipline.
• 10–15+ years of experience in data, analytics, business intelligence, cloud, or related technology domains.
• 7–10+ years of experience designing and delivering enterprise-scale AWS data platforms.
• Proven experience defining modern data strategies and cloud-based data architectures.
• Demonstrated experience providing technical leadership across complex data and analytics initiatives.
• Strong experience working with business and technical stakeholders in enterprise environments.

Technical Skills

AWS Data & Analytics

Strong expertise in AWS data and analytics services, including experience with:

• Amazon S3
• AWS Glue
• Amazon Redshift
• Amazon Athena
• Amazon Kinesis
• AWS-based data integration and processing services

Data Architecture

• Strong understanding of enterprise data architecture.
• Experience designing data lake, data warehouse, and lakehouse architectures.
• Strong SQL and data modelling capabilities.
• Experience designing scalable data ingestion and transformation architectures.
• Understanding of batch, streaming, and near real-time processing patterns.

Cloud Security & Governance

• Strong understanding of AWS IAM and access management.
• Experience applying cloud security and data governance principles.
• Understanding of AWS networking considerations within data platform architectures.
• Experience with cost optimization and cloud resource governance.

Data Engineering & Platform Operations

• Experience with ETL/ELT pipelines and data integration.
• Understanding of data quality, metadata, and lineage practices.
• Experience with monitoring, performance tuning, and platform optimization.
• Understanding of CI/CD and automated deployment practices for cloud data platforms.
• Experience developing technical documentation and operational runbooks.

Leadership & Core Competencies

• Strong ability to provide technical direction and influence architecture decisions across multiple teams.
• Excellent business-to-technical translation skills.
• Strong stakeholder management and communication capabilities.
• Ability to lead architecture discussions, solution design sessions, and technical reviews.
• Strong analytical and problem-solving skills.
• Ability to establish reusable architecture patterns and drive technical consistency.
• Commercial awareness of cloud consumption and the ability to balance technical requirements with cost efficiency.
• Strong focus on security, governance, scalability, reliability, and operational readiness.
• Demonstrated ability to mentor and develop technical team members.
• Comfortable working across multidisciplinary and geographically distributed teams.

Preferred Certifications

• AWS Certified Solutions Architect – Professional or Associate
• AWS Certified Data Analytics – Specialty
• AWS Certified Machine Learning – Specialty or equivalent, where relevant to the role

AWS certifications are preferred but should complement demonstrated hands-on architecture and delivery experience.

What Success Looks Like

• AWS is established as a scalable, secure, governed, and well-architected modern data platform.
• Data pipelines and workloads are reliable, performant, and cost-efficient.
• Enterprise data is secure, governed, and readily accessible to authorized users.
• Data platforms effectively support analytics, reporting, data engineering, and applicable AI/ML workloads.
• Architecture standards and reusable patterns are consistently adopted across delivery teams.
• AWS infrastructure and data services are optimized for performance, reliability, and cost.
• Platform operations are stable, documented, and scalable.
• Technical teams have clear architectural direction and are equipped to deliver high-quality AWS data solutions.
• Business stakeholders receive practical guidance that enables effective adoption of AWS-based data capabilities.