Offer summary

Qualifications:

5+ years of experience in technical consulting or solution architecture with AWS-centric data solutions., Expertise in data lakes, warehousing, and pipelines, along with cloud data governance., AWS Data Engineer Associate, AWS Machine Learning Specialty, and AWS Solutions Architect Professional certifications are required., Proficient in Python, SQL, PySpark, and familiar with streaming technologies like Kafka or Kinesis..

Key responsibilities:

Lead the design and delivery of scalable, cloud-native data platforms for analytics, AI, and ML use cases.

Manage the assessment, design, and implementation of AWS data solutions while ensuring high quality and best practices.

Collaborate with cross-functional teams and provide expert-level support to stakeholders throughout the project lifecycle.

Create and maintain documentation for data architectures and lead technical workshops with customers.

Job description

It's fun to work in a company where people truly BELIEVE in what they're doing!

Job Description:

AWS Data Architect

About the Job

We have an excellent opportunity for an experienced AWS Data Architect to join our growing AWS Services team and help drive our expansion as a leading global AWS Partner. You’ll lead the design and delivery of scalable, cloud-native data platforms that support analytics, AI, and ML use cases. This role combines technical leadership with hands-on delivery across the full engagement lifecycle—from pre-sales and architecture through to implementation and handover. You’ll mentor others, lead strategic projects, and act as a trusted advisor to our clients. You should have 5+ years’ experience in technical consulting or solution architecture, with a proven track record in AWS-centric data solutions. Expertise in data lakes, warehousing, and pipelines is essential, with a strong understanding of cloud data governance. Familiarity with ML architectures and tools like Amazon SageMaker and Bedrock is a plus.

What you can expect to be doing as an AWS Data Architect:

Deliver individual consultancy engagements or contribute to larger projects by gathering requirements, analysing data, and proposing cloud-native solutions
Technically manage the assessment, design, and implementation of solutions
Ensure all consultancy work is delivered with high quality, consistency, and in line with best practices.
Highlight technical risks so that any Ingram Micro exposure to commercial loss can be minimised
Design and implement secure, high-performance AWS data platforms aligned to business and technical needs.
Build data models, ETL/ELT pipelines, and integration solutions using modern tools and frameworks.
Align data architectures with customer objectives, AWS well-architected principles, and industry standards.
Lead end-to-end data engineering initiatives, from discovery through to production deployment.
Collaborate with cross-functional teams to ensure successful project delivery.
Create and maintain documentation covering data architectures, technical processes, and standards.
Ensure smooth knowledge transfer and operational handover to support and delivery teams.
Provide expert-level support to internal and external stakeholders as required.
Lead technical workshops and presentations with customers to shape solutions and influence outcomes.

In order to set you up for success, we are looking for the following skills and experience:

AWS Data Engineer Associate Certification
AWS Machine Learning Speciality Certification
AWS Solutions Architect Professional Certification
Experience in data architecture/engineering, designing cloud-native data platforms.
Experience in delivering complex AWS solutions, including data lakes and pipelines.
Expert in AWS services like S3, Glue, Redshift, EMR, Lambda, and RDS.
Strong grasp of data modelling, including OLAP/OLTP and schema design.
Built ETL/ELT workflows with Glue, dbt, and orchestration tools (e.g., Airflow).
Proficient in Python, SQL, PySpark, and distributed processing with Spark.
Familiar with streaming tech such as Kafka or Kinesis.
Ability to Optimise data solutions for speed, scale, security, and cost.
Knowledge of MLOps pipelines for training and inference (e.g., SageMaker).
Familiar with ML architectures and foundation model developments

Make an application to join the team!

None of this is achievable without great people, with a complete customer focus.

Our team is as much about our people as it is our customers and business partners. We want associates with a strong desire to succeed. We offer an excellent base, commission, market leading incentives programme and clear career development. You will receive full training on the products you will be specialising in, and you will have access to a world leading catalogue of technology-based learning.

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