Data Architect - Canada Region

Slalom is a fiercely human business and technology consulting company that leads with outcomes to bring more value, in all ways, always. From strategy through delivery, our agile teams across 52 offices in 12 countries collaborate with clients to bring powerful customer experiences, innovative ways of working, and new products and services to life. We are trusted by leaders across the Global 1000, many successful enterprise and mid-market companies, and 500+ public sector organizations to improve operations, drive growth, and create value.

At Slalom, we believe that together, we can move faster, dream bigger, and build better tomorrows for all.

Job Title: Data Architect (For Vacant Role)

Who You’ll Work With

At Slalom, we co-create custom software, data, and cloud products with clients who are ready to accelerate their digital transformation. We’re passionate about technology and compelled by its potential — building digital products, experiences, and technology-driven organizations that drive true change.

Our Data Architecture & Engineering team sees data as the foundation for decision-making, artificial intelligence, and transformation. We embrace AI to scale with quality, innovate without fear, and use technology with purpose to unlock the full potential of data and create lasting impact.

We demonstrate every day that talent, creativity, and technical excellence have no borders by delivering world-class solutions that inspire people to dream big and move faster.

What You’ll Do

As a Data Architect at Slalom, you will work in collaborative teams to deliver innovative, scalable solutions across Amazon Web Services, Microsoft Azure, and Google Cloud Platform technologies. You’ll stay ahead of emerging technologies and help shape the next generation of data platforms for some of the most forward-thinking organizations in data and analytics.

Your day-to-day will include:

• Design and evolve data architectures for client environments by assessing current‑state systems and defining scalable, future‑state solutions
• Remain hands‑on with data engineering delivery, contributing directly to building, coding, and implementing data pipelines and platforms alongside the team
• Balance architectural ownership with execution, guiding technical direction while actively participating in day‑to‑day engineering work
• Collaborate closely with clients to understand requirements, constraints, and technical environments, translating business needs into effective data engineering and architecture solutions
• Lead and contribute to solution design and technical discovery, including early‑stage conversations and, where applicable, pre‑sales or proposal support
• Build and design solutions on modern cloud data platforms, working with cloud providers, data warehousing technologies, and distributed processing frameworks
• Focus on data engineering and data architecture outcomes, with minimal emphasis on BI or data visualization work
• Apply and exploreAI‑accelerated data engineering approaches, including the use of generative or AI‑enabled tools to improve speed, quality, and scalability of engineering and architecture tasks
• Adapt to project needs by starting engagements in an engineering capacity and progressively taking on deeper architectural ownership as solutions and teams mature

What You’ll Bring

• Strong experience as a hands‑on data engineer, with the ability to design, build, and maintain production‑grade data solutions while contributing directly to delivery
• Demonstrated experience in data architecture, including assessing existing client environments, designing scalable data platforms, and guiding technical decisions from design through implementation
• Experience working with modern cloud data ecosystems, including at least one major cloud provider (AWS, Azure, or GCP), and familiarity with data warehousing and distributed data processing technologies
• Ability to operate comfortably in client‑facing environments, translating business and technical requirements into clear, practical data architecture and engineering solutions
• Experience balancing architectural leadership with execution, remaining actively involved in engineering work rather than operating as a purely conceptual or oversight role
• Exposure to AI‑accelerated data engineering, including the use of generative or AI‑enabled tools to improve the speed, quality, and effectiveness of data architecture and engineering tasks
• Flexibility to start engagements in an engineering capacity and evolve into deeper architectural ownership as project needs and solution maturity require
• Experience in most, but not all, of the following is expected:
• Cloud Platforms & Warehouses — Amazon Redshift, Snowflake, GoogleBigQuery, Azure Synapse Analytics, Amazon EMR
• Big Data & Streaming — Apache Spark, Presto, Databricks, Amazon Kinesis, Apache Kafka
• Workflow & Orchestration — Apache Airflow, dbt, Dagster, Azure Data Factory
• Databases, Containers & ML — DynamoDB, Cosmos DB, MongoDB, Kubernetes, Amazon ECS, Amazon SageMaker, Azure ML Studio
• Programming Languages — Python, Java (object-oriented)
• Lead, mentor and develop high-performingData Architects and Data Engineers
• Strong communication skills, with the ability to collaborate effectively with engineers, architects, and client stakeholders across discovery, delivery, and solution design phases