AWS Architect

About us
DS Smith has grown significantly through recent years via acquisitive growth and as a result we have a number of different management and information systems scattered across the estate. We have similar but not identical systems that are doing similar functions in different regions. Therefore, as part of our global I&T strategy, DS Smith is seeking to accelerate the use of Digital, and Data technologies and processes to create value and enable organic growth. A key part of this is creating this "next generation" data infrastructure is the creation and operation of our Enterprise data Platform (which we call the "Data Factory") for the entire business to use to leverage and exploit our data. The Data Factory includes both the underpinning cloud architecture in which to store our data as well as the necessary tools (e.g. data extraction tools) and capabilities (e.g. data analytics) to exploit. For the cloud architecture we have selected AWS as our strategic cloud partner and the data tools and capabilities are being key 3rd parties.

About the role

You will design and implement solutions using a range of AWS infrastructure, including S3, Redshift, Lambda, Step Functions, DynamoDB, AWS Glue, RDS, Athena, Kinesis. We also widely use other tech such as Databricks, Airflow, Power BI, etc, so experience in them is desirable. You will liaise with project teams to define requirements and refine solutions for our data projects. The ideal candidate will have exposure to CI/CD processes, or at least be keen to learn – our clients love infrastructure as code, and we like our engineers to own the deployment of their work. We need people who can work independently; but we're a close-knit, supportive team – we like to learn new things and share our ideas.

Key responsibilities

You will be responsible for leading the design and development of our data solution's architecture. Leading data pipeline architecture and identifying optimal data integration technologies to consolidate data from disparate systems. Leveraging cloud data platforms to democratize analytical capabilities. Working cross-functionally with stakeholders, and in particular our Bas, to translate business needs into technical data requirements and provide expertise on how to best leverage data to meet their goals.

Key Accountabilities:

• Shaping & designing solutions (notably data analytics, data integration, data platform) leveraging AWS services including S3, Redshift, Lambda, Step Functions, DynamoDB, AWS Glue, RDS, Athena, and Kinesis for our Data Factory.

• Driving the performance of assurance activity to delivery appropriate quality.

• Collaborate with project teams to gather requirements, refine solutions, and scope data projects.

• Gain exposure to and willingness to learn CI/CD processes to enable infrastructure as code and ownership of solution deployment.

• Utilize additional technologies such as Databricks, Airflow, and Power BI to build robust data platforms and analytics capabilities.

• Define data architecture strategy and standards across systems and projects.

• Designing & developing data models aligned to the functional and non-functional requirements.

• Ensure solutions meet scalability, flexibility, compliance, and other key data architecture principles.

• Research and evaluate emerging technologies and methodologies to guide innovation on the organization's data strategy.

• Lead the design and development of enterprise-wide data architecture and infrastructure

• Define data standards, models, policies, flows, and integration processes to enable a scalable and unified Data Factory platform.

• Manage data pipeline architecture leveraging tools like AWS Glue, Airflow, Databricks, etc.

• Continuously monitor and optimize data infrastructure performance, costs, and reliability.

• Establish comprehensive data governance practices, including security, privacy, and compliance controls.

• Guide adoption of AI/ML capabilities by building trusted and well-governed data platforms.

About you

• Strong experience in designing enterprise data architectures and solutions

• Expertise with major cloud data platforms especially AWS

• Hands-on experience building and optimizing big data pipelines, data lakes, warehouses with tools like Spark, Kafka, Airflow, dbt, etc.

• Strong data modeling, database design, and SQL skills

• Experience with BI/analytics platforms like Tableau, Looker, Power BI

• Knowledge of data science disciplines like machine learning, AI, and statistical analysis

• Understanding of data governance best practices related to security, compliance, privacy, and lifecycle management

• Ability to communicate complex data concepts to business users and stakeholders

• Natural curiosity to explore and learn new technologies like streaming data, graph databases etc.

• Strategic thinker with ability to translate business needs into technology roadmaps and data capabilities

• Passion for making data-driven decisions and enabling data democratization

• Familiarity with agile software development methodologies